AN ADAPTIVE MODULATION SELECTION POLICY IN ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING BASED WIRELESS SYSTEMS

IBRAHIM ISMAIL MOHAMMED AL-KEBSI

THESIS SUBMITTED IN FULFILMENT FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

FACULTY OF ENGINEERING AND BUILT ENVIRONMENT UNIVERSITI KEBANGSAAN MALAYSIA

BANGI

2010

POLISI PEMILIHAN PEMODULATAN ADAPTIF DALAM SISTEM TANPA WAYAR BERASASKAN PEMULTIPLEKSAN PEMBAHAGIAN

FREKUENSI ORTOGON

IBRAHIM ISMAIL MOHAMMED AL-KEBSI

TESIS YANG DIKEMUKAKAN UNTUK MEMPEROLEH IJAZAH DOKTOR FALSAFAH

FAKULTI KEJURUTERAAN DAN ALAM BINA UNIVERSITI KEBANGSAAN MALAYSIA

BANGI

2010

ii

DECLARATION

I hereby declare that the work in this thesis is my own except for quotations and

summaries, which have been duly acknowledged.

22 September 2010 IBRAHIM ISMAIL MOHAMMED AL-KEBSI P34762

iii

ACKNOWLEDGMENTS

First, I am grateful to ALLAH s.w.t, the omniscient, for guiding me to conceptualize, develop and complete my PhD thesis. Indeed, without His help and will, nothing is accomplished. I am indebted to my supervisor, Professor Dr. Mahamod Bin Ismail and my co-supervisor, Professor Dr. Kasmiran Bin Jumari, who have initiated ideas, encouraged and given support during the periods of research, simulation, and writing thesis. I wish to extend my warmest thanks to all those who have helped me with my work in the Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (UKM). This research work was partially supported by PKT4/2008 research grant from Malaysian Communications and Multimedia Commission (MCMC). I would like to express my sincerest gratitude and appreciation to my family for their endless love and support during my life. Without their moral support, this thesis would never have been completed. I would like to express my gratitude to my scholarship sponsor from the Yemen's ministry of Higher education for financing of my study.

iv

ABSTRACT

Orthogonal Frequency Division Multiplexing (OFDM) is a technology used to compress a large amount of data into a small amount of bandwidth. Among challenges encounter by OFDM system is related to the selection policy of an appropriate modulation scheme for transmission in each subcarrier. In addition, identifying a compromise between Peak-to-Average Power Ratio (PAPR) improvement and reasonable Symbol Error Rate (SER) performance is the most important issue in OFDM system. Although Adaptive Modulation (AM) is a physical layer technique that can adjust modulation based on the channel condition, it is not good solution to enhance the system throughput. At each Signal-to-Noise Ratio (SNR) value, it cannot utilize more than one modulation scheme to map the data onto carriers, and this leads to constant system throughput if the channel condition does not change. This thesis proposes two models of modulation selection policy. The selection policy in the first model is controlled by SER. In this model, all available modulation schemes are utilized to map the input data at low SNRs but with different percentage of utilization based on SER that can be calculated from the last successful OFDM symbol transmission. However, in the second model, the selection policy is controlled by the values of SNR and SER but limited to two modulation schemes only. Furthermore, these two selection policy models are then combined with the clipping technique to produce an algorithm called Adaptive Modulation and Clipping (AMCl). The clipping technique in this algorithm serves to reduce the PAPR and to control the selection policy in each model by defining variant CRs depending on the modulation scheme order, SER, and SNR. AMCl also employs updating mechanism to define the value of CR at each new symbol transmission. AMCl in both models is built using Matlab code. The proposed models are tested and validated in three OFDM wireless systems; IEEE802.11g, 802.16e, and 4G. Simulation results show the ability of the proposed models to improve the PAPR, enhance the data rate at all SNRs, and provide good SER performance. For example, the OFDM-256QAM signal in IEEE802.16e at 10-3

is improved with 6 dB and 3.5 dB over normal system in PAPR and SER respectively. The data rate is enhanced from 7.9 to 38.1 Mbps at SNR of 5 dB.

v

ABSTRAK

Pemultipleksan Pembahagian Frekuensi Ortogon (OFDM) merupakan teknologi yang digunakan untuk memampatkan sejumlah data yang besar dalam lebar jalur yang sempit. Antara cabaran yang dihadapi oleh sistem OFDM adalah berkait dengan polisi pemilihan pemodulatan yang sesuai bagi penghantaran setiap subpembawa. Tambahan, isu terpenting dalam sistem OFDM adalah untuk mengenalpasti tolak ansur antara penambahbaikan Nisbah Kuasa Puncak-ke-Purata (PAPR) dan prestasi nilai Kadar Ralat Simbol (SER) yang sesuai. Walaupun Pemodulatan Adaptif (AM) merupakan teknik lapisan fizikal yang boleh mengubah pemodulatan berasaskan keadaan saluran, teknik ini bukanlah suatu penyelesaian yang baik bagi mempertingkatkan truput sistem. Ketika nilai Nisbah Isyarat-ke-Hingar (SNR) adalah malar, teknik ini tidak dapat menggunakan lebih dari satu skema pemodulatan bagi memeta data ke atas pembawa, dan hal ini akan menghasilkan truput sistem yang malar jika keadaan saluran masih tidak mengalami perubahan. Tesis ini mencadangkan dua model pemilihan pemodulatan. Polisi pemilihan dalam model pertama dikawal oleh SER. Dalam model ini, semua skema pemodulatan yang boleh disediakan akan digunakan bagi memeta data masukan pada nilai SNR yang rendah tetapi dengan peratusan penggunaan yang berbeza berdasarkan nilai SER yang boleh dikira dari simbol OFDM terakhir yang berjaya dihantar. Namun dalam model kedua pula, polisi pemilihan dikawal oleh nilai-nilai SNR dan SER tetapi terhad kepada dua skema pemodulatan sahaja. Di samping itu, kedua-dua model polisi ini kemudian digabungkan dengan teknik pengetipan bagi menghasilkan algoritma yang dinamakan Pemodulatan Adaptif dan Pengetipan (AMCl). Teknik pengetipan dalam algoritma ini bertujuan mengurangkan PAPR dan untuk mengawal polisi pemilihan dengan mentakrifkan pelbagai Nisbah Pengetipan (CRs) bergantung kepada tertib skema pemodulatan, SER dan SNR. AMCl juga menggunakan mekanisma pengemaskinian untuk mentakrifkan nilai CR pada setiap penghantaran simbol baru. AMCl pada kedua-dua model yang dibina menggunakan kod Matlab. Model yang dicadangkan telah diuji dan disahkan dalam tiga sistem tanpa wayar OFDM; IEEE802.11g, 802.16e dan 4G. Hasil penyelakuan menunjukkan model yang dicadangkan berupaya memperbaiki PAPR, mempertingkatkan kadar data pada semua nilai SNR dan memberikan prestasi SER yang baik. Contohnya, isyarat OFDM-256QAM bagi IEEE802.16e pada 10-3

telah ditambahbaik masing-masing sebanyak 6 dB dan 3.5 dB berbanding sistem normal dari segi PAPR dan SER. Kadar data meningkat dari 7.9 ke 38.1 Mbps pada SNR bernilai 5 dB.

vi

CONTENTS

Page

DECLARATION ii

ACKNOWLEDGMENTS iii

ABSTRACT iv

ABSTRAK v

CONTENTS vi

LIST OF SYMBOLS x

LIST OF ABBREVIATIONS xii

LIST OF FIGURES xiv

LIST OF TABLES xviii

CHAPTER I INTRODUCTION

1.1 Introduction 1

1.2 Orthogonal Frequency Division Multiplexing (OFDM) 3

1.3 Problem statement 5

1.4 Thesis objectives 7

1.5 Thesis contribution 8

1.6 Thesis scope and limitation 9

1.7 Thesis methodology 9

1.8 Thesis organization 11

CHAPTER II LITERATURE REVIEW

2.1 Introduction 12

2.1.1 The concept of multicarrier modulation 13 2.1.2 OFDM as multicarrier modulation 14 2.1.3 Evolution of OFDM 15 2.1.4 Applications of OFDM 17 2.1.5 OFDM system design issues 20 2.1.6 OFDM system design requirements 20 2.1.7 OFDM system design parameters 21

2.2 OFDM transceiver systems 22

2.2.1 OFDM modulation and demodulation 25 2.2.2 QAM mapping 28 2.2.3 OFDM implementation by FFT 32

vii

2.2.4 Intersymbol and intercarrier interference 35 2.2.5 Guard time and cyclic extension 37

2.3 Peak power problem 40

2.3.1 PAPR of OFDM 40 2.3.2 Reasons for reducing PAPR in OFDM 40 2.3.3 PAPR calculation in OFDM 42 2.3.4 Distribution of PAPR 43 2.3.5 Effects of PAPR 44

2.4 PAPR reduction techniques 44

2.4.1 Clipping and filtering technique 46 2.4.2 Significance of clipping technique 48

2.5 Adaptive modulation 49

2.5.1 Conventional Adaptive modulation for OFDM 50 2.5.2 Chanel quality estimation 52 2.5.3 Choice of the modulation schemes 56 2.5.4 Conventional modulation selection algorithm 56 2.5.5 Signaling and blind detection 60 2.5.6 Adaptation benefits 62 2.5.7 Adaptation boundaries 63 2.5.8 Limitations of adaptive modulation 65 2.5.9 Theoretical performance of adaptive modulation 66 2.5.10 Parameters adaptation 67 2.5.11 Constant throughput adaptive OFDM 71

2.6 Summary 72

CHAPTER III METHODOLOGY

3.1 Introduction 73

3.1 Verified systems 75

3.2 Calculation of OFDM parameters 77

3.3.1 Oversampling 79 3.3.2 Zero padding 80 3.3.3 Implementation complexity reduction 81 3.3.4 2N-IFFT 82

3.3 The clipping ratio 82

3.5 Complementary cumulative distribution function 84

3.6 Signal to noise ratio 87

3.7 Error vector magnitude 88

3.8 Symbol error rate 90

3.9 The proposed adaptive modulation selection models 92

viii

3.10 The proposed system models 93

3.10.1 The algorithm AMCl in model (1) 95 3.10.2 CR definition mechanism in model (1) 99 3.10.3 The algorithm AMCl in Model (2) 102 3.10.4 CR definition mechanism in model (2) 105 3.10.5 Data rate calculation in proposed models (1) and (2) 106 3.10.6 The complexity of AMCl algorithm 107

3.11 Summary 107

CHAPTER IV ADAPTIVE MODULATION SELECTION POLICY MODELS

4.1 Introduction 109

4.2 Performance of normal OFDM system 111

4.2.1 Order of modulation scheme 111 4.2.2 Cyclic prefix and number of subcarriers 115 4.2.3 Processing and multipath delay 124

4.3 Effects of clipping ratio (CR) 130

4.3.1 CR and the modulation schemes order 130 4.3.2 CR and percentage of the clipped samples 132 4.3.3 CR and SER performance 135

4.4 Out-of-band radiation 145

4.5 In-band distortion 148

4.5.1 Error performance of clipped passband OFDM signal 148 4.5.2 EVM of the clipped passband OFDM signal 149

4.6 The utilization percentage in model (1) 151

4.7 The utilization percentage in model (2) 154

4.8 Summary 159

CHAPTER V THE PERFORMANCE OF AMCl IN OFDM BASED WIRELESS SYSTEMS

5.1 Introduction 160

5.2 The selection policy of AMCl in model (1) 161

5.3 The selection policy of AMCl in model (2) 174

5.4 Validation of AMCl in model (1) 177

5.4.1 SER performance 177 5.4.2 Improvement in PAPR 187 5.4.3 Throughput enhancement 193

ix

5.5 Validation of AMCl in model (2) 202

5.5.1 SER performance comparison 202 5.5.2 PAPR reduction 207 5.5.3 Data rate enhancement 211

5.6 Cost function of algorithm AMCl 217

5.7 Summary 218

CHAPTER VI CONCLUSIONS AND FUTURE WORK

6.1 Introduction 222

6.2 Conclusions 222

6.5 Future work 225

REFERENCS 226

APPENDICES

A List of publications 234

x

LIST OF SYMBOLS

k Carrier number

l OFDM symbol number

m Transmission frame number

N Number of transmitted carrier

N Number of signaling symbols per subband s

T Symbol duration s

T Inverse of the carrier spacing U

T’ Duration of a data symbol

f Central frequency of the radio frequency (RF) signal c

k’ Carrier index relative to the center frequency

c Complex symbol for carrier k of the Data symbol no. n in frame number

m,n,k

α Minimum distance separating two constellation points

C Number of points in a constellation

τ Delay spread max

F OFDM frame

f Doppler frequency D

A Clipping level

z Peak threshold value

σ Root mean squared power of the unclipped OFDM signal

S Average signal power

P Total signal power

P BER performance in an AWGN channel G

pb Bit error probability

γ Signal to Noise Ratio (SNR)

l SNR thresholds between the modulation schemes i

M Number of the signal constellation states

B Average spectral efficiency

η Spectral efficiency

R Signal data rate

V Average voltage of the signal modulation constellation

xi

X Transmitted data symbol on the n-th subcarrier n

E Average energy per bit av

xii

LIST OF ABBREVIATIONS

ADC Analog-to-Digital Converter

ADSL Asymmetrical Digital Subscriber Line

AM Adaptive Modulation

AMC Adaptive Modulation and Coding

AMCl Adaptive Modulation and Clipping

AOFDM Adaptive OFDM

ATM Asynchronous Transfer Mode

AWGN Additive White Gaussian Noise

BPSK Binary Phase Shift Keying

BWIF Broadband Wireless Internet Forum

CCDF Complementary cumulative distribution function

CP Cyclic prefix

CR Clipping Ratio

CSI Channel State Information

DAB Digital Audio Broadcasting

DAC Digital-to-Analog Converter

DER Detection Error Ratio

DFFT Discrete Fast Fourier Transform

DTV Digital Television (based on MPEG-2 video signal)

DSP Digital Signal Processing

DVB Digital Video Broadcasting

DVB-T Digital Video Broadcasting-Terrestrial

DUT Device Under Test

ETSI European Telecommunication Standards Institute

EVM Error Vector Magnitude

FDD Frequency Division Duplex

FEC Forward Error Correction

FFT Fast Fourier Transform

HPA High Power amplifier

IBI Inter-block interference

IBO Input Back-Off

xiii

ICI Inter-Carrier Interference

IEEE Institute of Electrical and Electronics Engineers

IFFT Inverse Fast Fourier Transform

IMT International Mobile Telecommunications

ITU

ISI

International Telecommunications Union

Inter-Symbol Interference

LAN Local Area Network

LCR Level Crossing Rate

MPEG Moving Picture Experts Group

MC-CDMA Multi-Carrier Code Division Multiple Access

OBO Output Back-Off

OFDM Orthogonal Frequency Division Multiplexing

PAPR Peak to Average Power Ratio

PSAM

PDF

Pilot Symbol Assisted Modulation

Probability Density Function

PMEPR Peak-to-Mean Envelop Power Ratio

PSD Power Spectral Density

QAM Quadrature Amplitude Modulation

QPSK Quaternary Phase Shift keying

RMS Root-Mean-Square

RSSI Received Signal Strength Indicator

SER Symbol Error Rate

SFN Single Frequency Network

SDH Synchronous Digital Hierarchy

SIR Signal-to-Interference Ratio

SNR Signal-to-Noise Ratio

TPS Transmission Parameter Signaling

WAP Wireless Application Protocol

WiMAX

ZP

Worldwide Interoperability for Microwave Access

Zero Padding

xiv

LIST OF FIGURES

Figure No. Page

1.1 Methodology of AMCl in modulation selection policy models

10

2.1 OFDM System Block Diagram 24

2.2 OFDM modulation block diagram 26

2.3 OFDM demodulation block diagram 27

2.4 QAM principle 28

2.5 Constellation of different QAM schemes with α=1 30

2.6 Constellation of different non uniform QAM schemes with α=2

31

2.7 Constellation of different non uniform QAM schemes with α=4

32

2.8 OFDM implementation with IFFT/FFT 33

2.9 Model of each FFT stage used in the Matlab simulations 34

2.10 CCD of real components within the IFFT structure 35

2.11 Spectra of four orthogonal and non-orthogonal subcarriers 36

2.12 Received OFDM symbols in a multipath channel 38

2.13 Cumulative Distribution Function of PAPR 43

2.14 Effects of clipping on OFDM signal 46

2.15 Clipping and filtering 47

2.16 The conventional Modulation selection policy 51

2.17 Signalling scenarios in adaptive modems 69

3.1 Construction of a CCDF curve 85

3.2 CCDF curve of a typical OFDM signal 86

3.3 CCDF curves of a 4QAM signal and a 16-QAM signal 87

3.4 Measurement of EVM 90

3.5 OFDM block diagram with the proposed modulation selection policy in AMCl

94

3.6 The proposed Modulation selection policy 96

3.7 AMCl algorithm in model (1) 98

3.8 AMCl algorithm in model (2) 104

xv

4.1 SER performance of normal OFDM-IEEE 802.16e system with different order of modulation schemes

111

4.2 Scatter plots of normal OFDM-IEEE 802.16e system with different modulation schemes

114

4.3 Scatter plots of normal OFDM-4QAM-IEEE 802.16e system with different CP length

117

4.4 Scatter plots of normal OFDM-64QAM-IEEE 802.16e system with different CP length

119

4.5 Scatter plots of normal OFDM-256QAM-IEEE 802.16e system with different CP length

120

4.6 Scatter plots of normal OFDM-16-QAM-IEEE 802.16e with different number of sub-carriers at SNR of 10 dB

123

4.7 Time Response of the transmitted and received signals of normal IEEE 802.16e System

126

4.8 Correlation of transmitted and received OFDM IEEE80216e signals

127

4.9 Effect of multipath on the IEEE 802.16e of OFDM received baseband signal

128

4.10 Scatter plots of normal OFDM- IEEE 802.16e-16QAM system with/without Zero Padding

129

4.11 Clipping ratio as function of the modulation schemes order 131

4.12 CR definition mechanism in the proposed modulation selection models

132

4.13 PAPR of normal OFDM-256QAM-IEEE 802.16e signal with as a function of CR

136

4.14 SER of the clipped OFDM-IEEE 802.16e signal for different CRs with different modulation schemes

138

4.15 PSD of the clipped OFDM-IEEE 802.16e signal with 4-QAM at various CRs

141

4.16 PSD of the clipped OFDM-IEEE 802.16e signal with16-QAM at various CRs

142

4.17 PSD of the clipped OFDM-IEEE 802.16e signal with 64-QAM at various CRs

143

4.18 PSD of the clipped OFDM-IEEE 802.16e signal with 256-QAM at various CRs

144

4.19 PSD of the normal and clipped OFDM- IEEE 802.11g signals with 256-QAM

146

4.20 PSD of the normal and clipped-filtered OFDM- IEEE 802.11g signals with 256-QAM

146

xvi

4.21 PSD of normal and clipped OFDM- IEEE 802.16e signals with 256-QAM

147

4.22 PSD of normal and clipped-filtered OFDM- IEEE 802.16e signals with 256-QAM

147

4.23 The effect of In-band distortion on SER performance of OFDM-DVB-T-256QAM system

149

4.24 EVM of normal, clipped passband and clipped digital OFDM-DVB-T-256QAM

150

4.25 The utilization percentage of modulation schemes in model (1)

152

4.26 The utilization percentage of modulation schemes in model (1)

155

5.1 The distribution policy of modulation schemes in proposed mode (A)

168

5.2 Utilization percentages of 256-QAM in the verified OFDM systems

173

5.3 SER performance of normal, clipped OFDM- IEEE802.11g signal with 256QAM, 128QAM and proposed modes (A) and (B)

179

5.4 SER performance of normal, clipped OFDM- IEEE802.11g signal with 64-QAM and proposed mode (C)

180

5.5 SER performance of normal OFDM-IEEE 802.16e signal with 4,16, 128, 256-QAM and proposed mode (F)

182

5.6 SER Performance of Normal OFDM-IEEE 802.16e Signal with 4, 16,64, and 256-QAM and Proposed Mode (G)

183

5.7 SER performance of normal, clipped OFDM-4G signal with 256-QAM and proposed modes (F) and (G)

185

5.8 SER performance of normal OFDM-4G signal with 64-QAM and proposed mode (C)

186

5.9 CCDF of PAPR for normal OFDM-IEEE802.11g Signal with 256-QAM, 4QAM and proposed modes (A), (B), and (C)

188

5.10 CCDF of PAPR for normal OFDM-IEEE 802.16e signal with BPSK,16, 64, 128, 256-QAM and proposed modes (F), and (G)

190

5.11 CCDF of PAPR for normal OFDM-4G signal with 256-QAM and proposed modes (B), (F), and (G)

191

xvii

5.12 CCDF of PAPR for normal OFDM-4G signal with 64-QAM and proposed mode (C)

192

5.13 Throughput of OFDM-IEEE 802.11g with Conventional AM and proposed modes (A), and (B)

195

5.14 Throughput of OFDM-IEEE 802.16e with conventional AM and proposed modes (F), and (G)

197

5.15 Throughput of the conventional AM in OFDM-4G system and two proposed modes A, and B

200

5.16 SER performance of Mode (D) with high and low CRs 203

5.17 SER performance of Mode (E) with high and low CRs 204

5.18 SER performance of the normal OFDM-IEEE 802.11g signal and proposed modes (D) and (E) with high CR

205

5.19 SER performance of the normal OFDM-4G signal and proposed modes (D) and (E)

206

5.20 CCDF of PAPR for normal and clipped OFDM- IEEE802.11g with 256-QAM at high and low CRs

208

5.21 CCDF of PAPR for normal and clipped OFDM-IEEE802.11g with 128 and 64-QAM at high and low CRs

208

5.22 CCDF of PAPR for normal and clipped OFDM- IEEE802.11g with16 and 4-QAM at high and low CRs

209

5.23 CCDF of PAPR for normal and clipped OFDM-4G with 4 and 256-QAM at different CRs

211

5.24 Throughput of OFDM-IEEE 802.11g with conventional AM and proposed modes (E), and (D) with low CR

214

5.25 Throughput of OFDM-IEEE 802.11g with conventional AM and proposed modes (E), and (D) with high CR

214

xviii

LIST OF TABLES

Table No. Page

2.1 Comparison of Parallel and Serial Transmission Schemes 16

2.2 Modulation supported in IEEE 802.11g 18

2.3 Modulation supported in IEEE 802.11e 19

2.4 Modulation supported in DVB-T 20

2.5 Optimized switching levels for adaptive modulation 57

2.6 Conventional modulation selection algorithms in AM 59

2.7 AWGN switching thresholds 65

3.1 Simulation parameters of tested systems 76

3.2 Desired requirements of the verified systems 77

3.3

The proposed models and modes of selection policy 92

3.4 SER switching values of modulation selection policy in model (1)

97

3.5 Clipping ratio definitions in AMCl of model (1) 100

3.6 Clipping ratio definitions in the tested mode (A) 101

3.7 Clipping ratio definitions in AMCl of model (2) 106

4.1 AWGN switching thresholds for conventional selection policy

112

4.2 Percentages of Clipped OFDM-DVB-T Samples at Different CRs

134

4.2 Classification of CRs based on the percentage of clipped 135 samples in OFDM-DVB-T system

4.4 SER degradation of normal OFDM-IEEE 802.16e signal 139 at moderate CRs with different modulation schemes

4.5 EVM Percentages at Different SNRs for Various 151 Modulation Schemes

4.6 Utilization percentages of modulation schemes in model (1) 153

4.7 Utilization percentages of modulation schemes in model (2) with low CR

156

4.8 Utilization percentages of modulation schemes in model (2) with high CR

156

xix

4.9 Utilization equations at various SNRs in model (2) with low CR

157

4.10 Utilization equations at various SNRs in model (2) with high CR

158

5.1 Percentages of modulated subcarries in mode (A) of OFDM-IEEE 802.11g system (case 1)

164

5.2 Percentages of modulated subcarries in mode (A) of OFDM-IEEE 802.11g system (case 2)

164

5.3 Percentages of modulated subcarries in mode (B) of OFDM-IEEE 802.11g system

165

5.4

Percentages of modulated subcarries in mode (G) of OFDM-IEEE 802.11g system

165

5.5 Percentages of modulated subcarries in mode (H) of OFDM-IEEE 802.11g system

165

5.6 Percentages of modulated subcarries in mode (I) of OFDM-IEEE 802.11g system

166

5.7 SER switching values of modulation selection policy in mode (A)

167

5.8 Percentages of modulated subcarries in mode (F) of OFDM-IEEE 802.11e system

169

5.9 Percentages of modulated subcarries in mode (G) of OFDM-IEEE 802.11e system

170

5.10 Percentages of modulated subcarries in mode (F) of OFDM-4G system

171

5.11 Percentages of modulated subcarries in mode (G) of OFDM-4G system

172

5.12 Definitions of CRs in model (2) 174

5.13 Percentages of modulated subcarriers in mode (D) of OFDM-IEEE802.11g system

176

5.14 Percentages of modulated subcarriers in mode (E) of OFDM-IEEE802.11g

176

5.15 SER improvements at different SER levels of OFDM- IEEE 806.11g for tested modes (A), (B), and (C) in model (1)

181

5.16 SER improvements at different SER levels of OFDM- IEEE 802.16e for tested modes (F), and (G) in model (1)

184

5.17 SER improvements at different SER levels of OFDM-4G for tested modes (C), (F), and (G) in model (1)

187

xx

5.18 PAPR Improvements in OFDM-IEEE802.11g at probability of 10-3

189 in tested modes (A), (B), and (C)

5.19 PAPR Improvements in OFDM-IEEE802.11e at probability of 10-3

190 tested modes (F), and (G)

5.20 PAPR improvements in OFDM-4G at probability of 10-3

192 in tested modes (B), (C), (F), and (G)

5.21

Data Throughput of Tested Modes in IEEE 802.11g 194

5.22 Comparisons between the required transmission times in normal OFDM-IEEE802.11g and proposed modes (A), (B), and (C) at different SNRs

196

5.23 Data Throughput of Tested Modes in IEEE 802.11e 197

5.24 Comparisons between the required transmission times in normal OFDM-IEEE 802.16e and proposed Mode (F) at different SNRs

198

5.25 Comparisons between the required transmission times in normal OFDM-IEEE 802.16e and proposed Mode (G) at different SNRs

198

5.26 Data Throughput of Tested Modes in 4G 199

5.27 Comparisons between the required transmission times in normal OFDM-4G and proposed mode (F) at different SNRs

201

5.28 Comparisons between the required transmission times in normal OFDM-4G and proposed mode (G) at different SNRs

201

5.29 PAPR Improvements compared to normal OFDM- IEEE 802.11g at probability of 10-3

modes (D), and (E) in proposed

210

5.30 Comparisons between the required transmission times of the normal OFDM- IEEE802.11g and proposed mode (D) at different SNRs

215

5.31 Comparisons between the required transmission times of the normal OFDM-IEEE802.11g and proposed mode (E) at different SNRs

216

5.32 Overall performance improvements in some tested modes of AMCl in model (1)

219

5.33 Overall performance improvements in some tested modes of AMCl in model (2)

220

5.34 Comparison between the two proposed modulation selection policy models

221

CHAPTER I

INTRODUCTION

1.1 INTRODUCTION

Today, wireless technologies and systems which are claimed to be fourth generation

(4G) represent a market positioning statement by different interest groups. Such

claims must be substantiated by a set of technical rules in order to qualify as 4G.

Currently, the ITU (International Telecommunications Union) has been working on a

new international standard for 4G, called IMT-Advanced, which is regarded as an

evolutionary version of IMT-2000, the international standard on 3G technologies and

systems (Wang, et al 2009). Development of IMT-Advanced standards is likely to be

completed by 2010, with deployment expected around 2015 (Du & Swamy 2010).

At the present time, the research community and industry in the field of

telecommunications are considering possible choices for solutions in the fourth

generation (4G) of wireless communications. Long term researches and developments

are usually required to lead a commercial service to success. Now, just coming into

the new century, it might be a good time to start discussions on 4G systems, which

may be put in service around 2010 (Chuang & Sollenberger 2000). Indeed, since the

beginning of this century, the words future generation, and beyond 3G or 4G have

often seen in magazines on wireless communications (Lu & Berezdivin 2002). The

commercial rollout of these systems is likely to begin around 2008 - 2012, and will

replace 3G technology.

2

Few of the aims of 4G networks have yet been published, however it is likely

that they will be to extend the capabilities of 3G networks, allowing a greater range of

applications, and improved universal access. The spectral efficiency of 3G networks is

too low to support high data rate services at low cost (Hara & Prasad 2003). As a

consequence one of the main focuses of 4G systems will be to significantly improve

the spectral efficiency. According to the Vision Preliminary Draft of New

Recommendation (DNR) of ITU-R WP8F (Mohr & Nakagawa 2002), there will be a

steady and continuous evolution of IMT-2000 to support new applications, products,

and services.

For systems beyond 3G (beyond IMT-2000 in the ITU), there may be a

requirement for a new wireless access technology for the terrestrial component around

2010. This will complement the enhanced IMT-2000 systems and the other radio

systems with which there is an interrelationship. It is envisaged that these potential

new radio interfaces will support up to approximately 100 Mbps for high mobility and

up to approximately 1 Gbps for low mobility such as nomadic/local wireless access by

around 2010. Due to the high data rate requirements, additional spectrum will be

needed for these new capabilities of systems beyond IMT-2000.

In addition to high data rates, future systems must support a higher Quality Of

Service (QOS) than current cellular systems, which are designed to achieve 90 to 95%

coverage (Nanda, et al 2000). Some technology components required for 4G are well

known or already developed but might need tuning and improvements. Interference

management, forward error correction (FEC), mesh networking, and robust QOS are a

few examples to consider. OFDM also becomes a key technology because 4G relies

on the increased spectrum capacity within a given spectrum, frequency, code, and

time multiplexing and/or diversity, as well as a multi-carrier modulation scheme

(Tjelta, et al. 2001) & (NTT 2000).

3

1.2 ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING

Orthogonal frequency division multiplexing (OFDM) is well-known to be effective

against multipath distortion. It is a multicarrier communication scheme, in which the

bandwidth of the channel is divided into subcarriers and data symbols are modulated

and transmitted on each subcarrier simultaneously. By inserting guard time that is

longer than the delay spread of the channel, an OFDM system is able to mitigate

intersymbol interference (ISI). Deploying an adaptive antenna array at the receiver can

help separate the desired signal from interfering signals which originate from different

spatial locations. This enhancement of signal integrity increases system capacity (Bing

2002). Although OFDM has only recently been gaining interest from

telecommunications industry, it had a long history of existence. It is reported that

OFDM based systems were in existence during the Second World War. OFDM had

been used by US military in several high frequency military systems such as

KINEPLEX (Moiser & Calbaugh 1958), ANDEFT (Porter 1968) and KATHRYN

(Zimmerman & Kirsch 1967).

The concept of using parallel data transmission by means of frequency

division multiplexing (FDM) was published in mid 60s (Chang 1966; Salzberg 1967).

In December 1966, Chang outlined a theoretical way to transmit simultaneous data

stream through linear band limited channel without Inter Symbol Interference (ISI)

and Intercarrier Interference (ICI). Until this time, a large number of subcarrier

oscillators are needed to perform parallel modulations and demodulations. A major

breakthrough in the history of OFDM came in 1971 when Weinstein and Ebert used

Discrete Fourier Transform (DFT) to perform baseband modulation and

demodulation. All the proposals until this time used guard spaces in frequency domain

and a raised cosine windowing in time domain to combat ISI and ICI. Another

milestone for OFDM history was when Peled and Ruiz (1980) introduced Cyclic

Prefix (CP). In the 1990s, OFDM was exploited for wideband data communications

over mobile radio FM channels, High-bit-rate Digital Subscriber Lines (HDSL),

Asymmetric Digital Subscriber Lines (ADSL) and Very-high-speed Digital Subscriber

Lines (VDSL).

4

By 1992, Digital Audio Broadcasting (DAB) was proposed and the standard

was formulated in 1994. DVB along with High-Definition TeleVision (HDTV)

terrestrial broadcasting standard was published in 1995. At the dawn of the 20th

century, several Wireless Local Area Network (WLAN) standards adopted OFDM on

their physical layers. HiperLAN/2 was defined in June 1999. Perhaps, the greater

importance is the emergence of HiperLAN/2 technology as a competitor for future 4G

wireless systems. These systems, expected to emerge by the year 2012, promise to

deliver on the wireless Nirvana of anywhere, anytime, anything communications

(Nassar, et al. 2002). OFDM has several advantages make it a viable alternative for

CDMA in future wireless networks. These advantages included multipath delay

spread tolerance, immunity to frequency selective fading channels, high spectral

efficiency, efficient modulation and demodulation, and frequency diversity.

However OFDM suffers from problems such as orthogonality,

synchronization, phase noise, frequency error, co-channel interference in cellular

OFDM, and peak to average power ratio (PAPR). When the phase of different OFDM

subcarriers adds up to form large peaks, an important complication comes in OFDM

systems, this problem is called PAPR. In OFDM systems PAPR can have very high

values for certain input sets of sample and overload non-linear characteristics of

systems, causing inter-modulations among different carriers. Clipping is a

straightforward method to control the PAPR and it happens at the transmitter side.

Clipping an oversampled signal provides an efficient PAPR reduction. The overall

PAPR can be significantly reduced by selecting a proper clipping ratio (CR).

Unfortunately clipping causes nonlinear in-band distortions and sometimes out-of-

band radiation. Adaptive Modulation (AM) is a technique used to provide more user

capacity over the air during good propagation conditions, where the modulation level

of the radio link adapts dynamically to the conditions of the path. Algorithms of AM

are used to provide robust and spectrally efficient transmission over flat fading

channels (Alouini, et al. 1999). Such algorithms work on the idea of first estimating

the channel and then feeding this estimate back to the transmitter, where the

transmission scheme is changed appropriate to the channel characteristics.

5

In the last years the modulation selection policy in AM has received significant

interest due to its importance to improve the throughput of OFDM based wireless

systems. AM has been shown to have significant benefits for high-speed wireless data

transmission when OFDM is employed. However, accurate channel state information

(CSI) is required at the transmitter to achieve the benefits. AM ensures the most

efficient modulation scheme is always used based on certain criteria and constraints.

The varying parameters can be the symbol transmission rate, transmitted power level,

constellation size, SER, or any combination of these parameters. The purpose of AM

is to maximize the resources of the wireless radio channel. The traditional

communication systems are built with an adequate link margin, which guarantees

system functionality even in worse case scenarios. The conventional selection policy

of the modulation schemes in AM is based on the estimated SNR. This policy cannot

promise any enhancement in the system throughput if the channel situation still

without change for long time.

1.3 PROBLEM STATEMENT

Adaptive modulation refers to modulation scheme adjustment based on the channel

condition to enable better throughput and improve the spectral efficiency of wireless

system. In other words adaptive modulation allows a wireless system to choose the

highest order modulation depending on the channel conditions. Different order

modulation schemes allow sending more bits per symbol and thus achieve higher

throughputs or better spectral efficiencies.

It should be noted, however as a higher modulation technique is used, a better

SNR is needed to overcome interference and maintain a tolerable error rate level. In

other words when using a modulation technique such as 256-QAM, better SNRs are

needed to overcome any interference and maintain a certain symbol error ratio (SER).

This means that the conventional modulation selection policy in AM divides SNRs to

groups of boundaries or thresholds. Each group has upper and lower limits that

represent a particular value of SNR.

6

Each utilized modulation scheme is assigned to one group to meet the system

performance requirements. In the case of all users are located in the same area away

from the base station, all subcarriers face the same channel condition; therefore the

estimated values of SNR for all subcarriers are approximately the same. Despite the

user changes its location within the same area, SNR still within the boundary or

thresholds of particular modulation scheme. This leads to constant throughput at some

SNRs that utilize one order of modulation scheme or if the SNR does not change for

the specified period. Another scenario could be faced when the transmitter receives

wrong estimation about SNR; this problem becomes worse if this value of SNR is

low.

The long observation of the quality of the received OFDM signal shows

improvement in SER of some subcarriers. This sudden improvement could be

happened due to moving some users to the boundary of next area that is more close to

the base station. This leads to the possibility of using higher modulation scheme in

these subcarriers to map the input data based on this sudden improvement in SER. It is

better to suggest using other performance metrics for modulation selection policy

instead of SNR. By proposing new models of selection policy, all available

modulation schemes can be utilized to modulate the OFDM symbol especially at low

SNRs. Beside these problems in AM, OFDM suffers from high PAPR. Many PAPR

reduction techniques have been proposed since last years. Clipping is the simplest

method that can reduce the power peaks (Bonaccorso, et al. 1999).

The simple concept behind this is to clip the power peaks that go beyond

predetermined level. Clipping has been thought to introduce error. But it actually

depends on careful selection of clipping level (Wang, et al. 2005). Clipping can reduce

the PAPR to the bearable degree, but meanwhile introduces the out-of-band power

leakage, which may bring out interference to the other users and systems to work well

(Yunjun, et al. 2000; Van Nee

1996; Kim et al. 2003). To avoid interference, filtering

has to be added after clipping. Clipping also causes decrease to the in-band power,

which causes degradation for the system SER performance because the information

contained in the clipped portion is lost.

7

However, unlike the out-of-band radiation, the in-band distortion cannot be

eliminated by the filtering process. In addition the inverse relationship between SER

performance and PAPR reduction is the most important issue in OFDM system.

Choosing appropriate CR is essential and difficult mission especially when clipping

OFDM signal at low CR (hard clipping) to get better improvement in PAPR. It is clear

that OFDM system needs to get reasonable PAPR improvement by clipping OFDM

signal at low CR.

1.4 THESIS OBJECTIVES

The main objectives of thesis are to propose a selection policy of the modulation

schemes in AM and identify a compromise between PAPR and SER. In order to

improve the performance of the OFDM based wireless systems in terms of low PAPR,

high data throughput and reasonable SER performance, several distinct objectives can

be outlined as follows:

1. To propose two models of selection policy of the modulation schemes in

AM.

2. To propose an algorithm that is called Adaptive modulation and clipping

(AMCl) by combining the two proposed models with the clipping

technique.

3. To propose a mechanism of defining and updating the values of clipping

ratio (CR) in AMCl algorithm.

4. To identify a compromise between reduction in PAPR and reasonable SER

performance.

5. To validate and evaluate the performance of AMCl algorithm in OFDM

based wireless systems.

8

1.5 THESIS CONTRIBUTION

Thesis focuses on the modulation selection policy in AM and the effect of clipping

process on OFDM performance. The main contributions of this thesis are as follows:

1. Proposing two models of modulation selection policy in AM. The selection

policy in the first model utilizes the modulation schemes based on SER,

whereas the modulation schemes in the second model are utilized based on

SER and SNR.

2. Combining these models with the clipping technique to produce an algorithm

called AMCl. This algorithm exploits the advantages of AM and clipping

technique to make compromise between the two opposite performance metrics

SER and PAPR. AMCl will try to reduce PAPR, achieve SER performance

that is comparable to unclipped OFDM system, and enhance the throughput of

OFDM system at all SNRs.

3. Utilizing all available modulation schemes in the first model at SNRs below 8

dB, then AMCl will discard the low order schemes from mapping process as

SNR is increased. However in the second model, AMCl utilizes only one or

two modulation schemes that have adjacent order at each SNR.

4. Employing a mechanism in AMCl to define and update the values of CR at

each new OFDM symbol transmission. In other words AMCl employs

updating mechanism to define the utilization percentage Up

of each

modulation scheme at all SNRs. AMCl in the first model defines and updates

the CR based on SNR, whereas CR in second model is defined based on the

target SER.

5. Implementing the AMCl algorithm in different modes in order to confirm its

viability in OFDM based wireless systems. Each mode utilizes five, four, or

three modulation schemes. Each tested mode should provide the verified

OFDM system with the preferable performance that it needs.

9

1.6 THESIS SCOPE AND LIMITATION

The research described in this thesis contributes to significantly investigating the

reciprocal relation between PAPR and SER. In addition it tries to solve the low

throughput of OFDM system at low SNRs due to utilizing low order modulation

schemes. Proposing two modulation selection policy models to solve this problem is

the first scope of this research.

The joint performance of the combination of models with the clipping

technique that is called AMCl algorithm will be validated and evaluated in OFDM

based wireless systems. AMCl will be implemented in different modes of OFDM

systems using Matlab program code.

The overall performance of the verified systems will be discussed and

compared with normal OFDM systems. The most important issue in AMCl algorithm

is defining appropriate CR. AMCl employs updating mechanism to define and update

the values of CR based on SER or SNR to achieve the target performance.

These proposed models will be built using Matlab code and evaluated in

OFDM based wireless systems. This thesis will study the possibility of employing the

AMCl in some OFDM based wireless system by investigation the performance of the

verified OFDM in terms of SER, PAPR, and data throughput.

1.7 THESIS METHODOLOGY

In order to achieve the aforementioned objectives the following methodology can be

outlined as shown in Figures 1.1.

10

Figure 1.1 Methodology of AMCl in Modulation Selection Policy Models

The methodology will be explained with more details in chapter 3.

Identifying the problem in the selection policy of AM

Propose two models of modulation selection policy in AM

Policy in 1st model is controlled by SER

Policy In 2nd model is controlled by SNR and SER

Choose the appropriate modulation scheme for mapping process based on the measured values of SER, SNR, or both

Combine the two models with the clipping technique to produce the AMCl algorithm

Suggest IEEE802.16e, IEEE802.11g, and 4G as verified OFDM based wireless systems and select their parameters for simulation

Validate and evaluate AMCl algorithm in different tested modes of wireless systems and implement system models using Matlab

Enhance the OFDM systems throughput, improve the PAPR, and offer SER performance comparable to normal OFDM system

Estimate and calculate the values of SNR and SER after each successful symbol transmission

Define and update the CR (low, moderate, or high) based on the modulation scheme order and the values of SER or SNR

Analyze the performance of the tested systems using SER, CCDF, PSD, EVM and the throughput criteria

11

1.8 THESIS ORGANIZATION

This thesis is organized into six chapters. The first chapter briefly introduces the

definition, advantages, weakness and history of OFDM. This chapter also states the

objectives and contributions of this thesis.

Chapter two contains the literature review that covers the evolution of OFDM

and the basic principles of OFDM systems. This chapter reviews the peak power

problem and its reduction techniques. The adaptive modulation and channel

estimation definition are also explained in details in this chapter.

Chapter three provides the methodology of the research study, including how

the data for the simulation are selected and used. In this chapter the two models of

adaptive modulation selection and the AMCl algorithm in two models are described in

details. The proposed method to eliminate the effects of the clipping techniques is

presented in this chapter.

In chapter four and five the results from the analysis of the proposed algorithm

AMCl in both models of modulation selection policy in AM are presented and

discussed.

Lastly, Chapter six contains the conclusions from the thesis, and

recommendations for follow-on research.

CHAPTER II

LITERATURE REVIEW

2.1 INTRODUCTION

OFDM is a special form of multi-carrier transmission where all the subcarriers are

orthogonal to each other. OFDM promises a higher user data rate transmission

capability at a reasonable complexity and precision. One of the main reasons to use

OFDM is to increase the robustness against frequency selective fading and

narrowband interference. In a single carrier system, a single fade or interferer can

cause the entire link to fail, but in a multicarrier system, only a small percentage of

subcarriers will be affected. Error correction coding can then be used to correct the

few erroneous subcarriers.

OFDM is a parallel transmission scheme, where a high-rate serial data stream

is split up into a set of low-rate substreams, each of which is modulated on a separate

subcarrier FDM. Thereby, the bandwidth of the subcarriers becomes small compared

with the coherence bandwidth of the channel; that is, the individual subcarriers

experience flat fading, which allows for simple equalization. This implies that the

symbol period of the substreams is made long compared to the delay spread of the

time-dispersive radio channel. By selecting a special set of orthogonal carrier

frequencies, high spectral efficiency is obtained because the spectra of the subcarriers

overlap, while mutual influence among the subcarriers can be avoided.

13

The derivation of the system model shows that by introducing a cyclic prefix

(the guard interval (GI)). The orthogonality can be maintained over a dispersive

channel. A major benefit of OFDM systems is their low cost of implementation, due

to the relatively simple components required. An OFDM system requires Digital

Signal Processing (DSP) hardware for the implementation of the IFFT and FFT

transformations. These processors are inexpensive and widely available, either as

stand-alone components or on FPGA hardware (Flarion 2003). An OFDM receiver

requires only one modulator and demodulator, in contrast with other multi-carrier

systems (Uysal 2006).

2.1.1 The Concept of Multicarrier Modulation

Multi-carrier modulation is one of the transmission schemes which are less sensitive

to time dispersion (frequency selectivity) of the channel (Tellado 2000). In multi-

carrier systems, the transmission bandwidth is divided into several narrow sub-

channels and data is transmitted parallel in these sub-channels. Data in each sub-

channel is modulated at a relatively low rate so that the delay spread of the channel

does not cause any degradation as each of the sub-channels will experience at

response in frequency. Although, the principles are known since early sixties, multi-

carrier modulation techniques, especially Orthogonal Frequency Division

Multiplexing (OFDM), gained more attention in the last ten years due to the increased

power of digital signal processors. Multicarrier modulation helps to reduce the

detrimental effects of multipath fading (Litwin 2003). Because of its robustness to

multipath, and the ease of implementation it in transmitters and receivers using the

fast Fourier transform (FFT), the MCM concept is growing rapidly in practical

importance. Multicarrier modulation is an idea which was introduced over three

decades ago and is of increasing interest today because it can now be implemented

using powerful integrated circuits optimized for performing discrete Fourier

transforms.

14

2.1.2 OFDM as Multicarrier Modulation

OFDM is a multi-carrier modulation technique that can overcome many problems that

arise with high bit rate communication, the biggest of which is the time dispersion. In

OFDM, the carrier frequencies are chosen in such a way that there is no interference

with other carriers in the detection of the information in a particular carrier when the

orthogonality of the carriers is maintained. The data bearing symbol stream is split

into several lower rate streams and these streams are transmitted on different carriers.

Since this increases the symbol period by the number of non-overlapping

carriers (sub-carriers), multipath echoes will affect only a small portion of the

neighboring symbols. Remaining ISI can be removed by cyclically extending the

OFDM symbol. The length of the cyclic extension should be at least as long as the

maximum excess delay of the channel. The subcarriers are orthogonal to each other

because when the waveforms are multiplied of any two subcarriers and integrate over

the symbol period the result is zero.

Multiplying the two sine waves together is the same as mixing these

subcarriers. This results in sum and difference frequency components, which will

always be integer subcarrier frequencies, as the frequency of the two mixing

subcarriers has integer number of cycles. Since the system is linear the result can be

integrated by taking the integral of each frequency component separately then

combining the results by adding the two sub-integrals.

The two frequency components after the mixing have an integer number of

cycles over the period and so the sub-integral of each component will be zero, as the

integral of a sinusoid over an entire period is zero. Both the sub-integrals are zeros and

so the resulting addition of the two will also be zero, thus the frequency components

have been established to be orthogonal to each other.

15

2.1.3 Evolution of OFDM

The use of Frequency Division Multiplexing (FDM) goes back over a century, where

more than one low rate signal, such as telegraph, was carried over a relatively wide

bandwidth channel using a separate carrier frequency for each signal. OFDM owes its

origin to FDM. The evolution of OFDM can be divided into three parts (Mosier &

Clabaugh 1958). There are consists of FDM, MC Communication and OFDM. In

FDM, each of the several low rate user signals is modulated with a separate carrier

and transmitted in parallel. FDM has been used for a long time to carry more than one

signal over a telephone line (Stallings 2007).

FDM is the concept of using different frequency channels to carry the

information of different users. Each channel is identified by the center frequency of

transmission. To ensure that the signal of one channel did not overlap with the signal

from an adjacent one, some gap or guard band was left between different channels.

Obviously, this guard band will lead to inefficiencies which were exaggerated in the

early days since the lack of digital filtering is made it difficult to filter closely packed

adjacent channels.

Thus, the separation of the users is in the frequency domain. In order to be able

to easily demodulate each user signal, the carriers are spaced sufficiently apart from

each other. Moreover, guard band has to be provided between two adjacent carriers so

that realizable filters can be designed. Hence, the spectral efficiency is very low. The

above idea can be easily extended to provide communication service for a user with

high rate data stream. The data stream can be split into N low rate data streams, and

modulated using N sub-carriers and transmitted over the channel (Quateck 2009).

It is important to compare this parallel transmission scheme with a single high

rate data transmission. The results of the comparison are tabulated in Table 2.1. It is of

interest to note that before equalizers were developed, the parallel transmission

method was the means of achieving high data rates over a dispersive channel, in spite

of its high cost and relative bandwidth inefficiency.

16

It is of interest to note that before equalizers were developed, the parallel

transmission method was the means of achieving high data rates over a dispersive

channel, in spite of its high cost and relative bandwidth inefficiency. From Table 2.1,

it could be noticed that the major disadvantages of the parallel transmission scheme

are that its bandwidth inefficient and that several modulators and demodulator blocks

are required.

Table 2.1 Comparison of parallel and serial transmission schemes

Transmission method Parallel Serial

Symbol time T Ts s

Rate

/N

1/T N/Ts

Total BW required

s

2×N/Ts + N×0.1/T(Assume Guard band = 0.1/T

s s

2×N/T)

Susceptibility to ISI

s

Less More

Source: Hazy 2004

In OFDM, these problems are overcome by (Van Nee & Prasad 2000):

a. Using orthogonal sub-carriers instead of widely spaced sub-carriers (i.e.,

carriers with guard band between them).

b. Using IFFT and FFT algorithms for implementing the modulation and

demodulation operations.

The concept of muticarrier (MC) communications uses a form of FDM

technologies but only between a single data source and a single data receiver. As

multicarrier communications was introduced, it enabled an increase in the overall

capacity of communications, thereby increasing the overall throughput. Referring to

MC as FDM, however, is somewhat misleading since the concept of multiplexing

refers to the ability to add signals together.

17

MC is actually the concept of splitting a signal into a number of signals,

modulating each of these new signals over its own frequency channel; multiplexing

these different frequency channels together in an FDM manner; feeding the received

signal via a receiving antenna into a demultiplexer that feeds the different frequency

channels to different receivers and combining the data output of the receivers to form

the received signal.

OFDM is the concept of MC where the different carriers are orthogonal to

each other. Orthogonal in this respect means that the signals are totally independent. It

is achieved by ensuring that the carriers are placed exactly at the nulls in the

modulation spectra of each other.

2.1.4 Applications of OFDM

OFDM has been chosen for several current and future communications systems all

over the world. It is well suited for systems in which the channel characteristics make

it difficult to maintain adequate communications link performance.

The primary applications are in multimedia push technology and in wireless

LAN. This section is going to discuss only the OFDM based wireless systems that is

tested in the proposed modulation selection models and recovery method.

a. IEEE 802.11g

IEEE802.11g is an amendment to the IEEE 802.11 specification that extended

throughput to up to 54 Mbps using the same 2.4 GHz band as 802.11b (IEEE 802.11g-

2003. 2007). This specification under the marketing name of Wi-Fi has been

implemented all over the world. 802.11g was the third modulation standard

for Wireless LAN

. The 802.11g standard is an extension of the 802.11b standard.

18

Details of making b and g work well together occupied much of the lingering

technical process. Like 802.11a, 802.11g uses OFDM for transmitting data. OFDM is

a more efficient means of transmission than Direct Sequence Spread Spectrum

(DSSS) transmission, which is used by 802.11b. When coupled with various

modulation types as tabulated in Table 2.2, 802.11g (like 802.11a) is capable of

supporting much higher data rates than 802.11b. The 802.11g standard adds 802.11a

OFDM transmission modes to the 802.11b standard.

Table 2.2 Modulation supported in IEEE 802.11g

Standard Modulation schemes

IEEE 802.11g BPSK, QPSK, 16QAM, 64QAM

b. IEEE 802.16e

IEEE 802.16e or Mobile WiMAX standard was ratified by the IEEE in late 2005 as a

potential to emerge as a real viable competitor to existing 3G technologies (IEEE Std.

802.16e 2006)

. This potential gained traction when South Korea elected to take IEEE

802.16e compatible standard called wireless broadband (WiBro - since renamed to

Mobile WiMAX) to market.

Mobile WiMAX is a broadband wireless solution that enables convergence of

mobile and fixed broadband networks through a common wide area broadband radio

access technology and flexible network architecture (WiMAX forum 2006). Scalable

OFDMA (SOFDMA) is introduced in the IEEE 802.16e Amendment to support

scalable channel bandwidths from 1.25 to 20 MHz (Yagoobi 2004).

The scalability is supported by adjusting the FFT size while fixing the sub-

carrier frequency spacing at 10.94 kHz. Since the resource unit subcarrier bandwidth

and symbol duration is fixed, the impact to higher layers is minimal when scaling the

bandwidth.

19

The Mobile WiMAX Air Interface adopts Orthogonal Frequency Division

Multiple Access (OFDMA) for improved multi-path performance in non-line-of-sight

environments. Mobile WiMAX systems offer scalability in both radio access

technology and network architecture, thus providing a great deal of flexibility in

network deployment options and service offerings.

Table 2.3 summarizes the coding and modulation schemes supported in the

Mobile WiMAX profile. Support for QPSK, 16QAM and 64QAM are mandatory in

the DL with Mobile WiMAX. In the UL, 64QAM is optional.

Table 2.3 Modulation supported in IEEE 802.16e

IEEE 802.16e DL UL

Modulation QPSK, 16QAM, 64QAM QPSK, 16QAM, 64QAM

c. Digital Video Broadcasting

Digital Video Broadcasting (DVB) is an ETSI standard for broadcasting Digital

Television over satellites, cables and thorough terrestrial (wireless) transmission. The

development of the DVB standards was started in 1993 (ETSI. 2000). DVB is a

transmission scheme based on the MPEG-2 standard, as a method for point to

multipoint delivery of high quality compressed digital audio and video. It is an

enhanced replacement of the analogue television broadcast standard, as DVB provides

a flexible transmission medium for delivery of video, audio and data services

(Reimers 1998).

Terrestrial DVB (DVB-T) as a digital transmission delivers data in a series of

discrete blocks at the symbol rate. The DVB-T OFDM modulation system uses multi-

carrier transmission, and includes the use of a Guard Interval. It allows the receiver to

cope with strong multipath situations. DVB-T operates in either of two modes called

2K and 8K modes with 1705 carriers and 6817 carriers respectively. It uses QPSK, 16

QAM, or 64 QAM sub-carrier modulation as listed in Table 2.4. It also uses pilot sub-

carriers for recovering amplitude and phase for coherent demodulation.

20

DVB-T is a standard for Digital Video Broadcasting developed by ETSI.

Digital Television has become one of most exciting developments in the area of

consumer electronics at the end of the millennium. High Definition TV concept and

products are already well understood and amazing picture quality in term of resolution

and color is phenomenal.

DVB-T offers about 24 Mbps to stationary receivers with directional antennas

and 12 Mb/s to mobile receivers with omnidirectional antennas (ETSI EN 300 421.

1997). In DVB-T, one HDTV-signal (bit-rate approx. 20 Mb/s) can be transmitted in

an 8 MHz frequency slot using the most efficient coding (64-QAM).

Table 2.4 Modulation supported in DVB-T

Standard Terrestrial DVB

Modulation QPSK, 16QAM, 64QAM

2.1.5 OFDM System Design Issues

System design always needs a complete and comprehensive understanding and

consideration of critical parameters. OFDM system design is of no exception, it deals

with some critical and often conflicting parameters. Basic OFDM philosophy is to

decrease data rate at the subcarriers, so that the symbol duration increases, thus the

multipaths are effectively removed.

This poses a challenging problem, as higher value for cyclic prefix (CP)

interval will give better result, but it will increase the loss of energy due to insertion of

CP. Thus, a tradeoff between these two must be obtained for a reasonable design.

2.1.6 OFDM System Design Requirements

OFDM systems depend on four system requirement (Tarokh 2009)

21

a. Available bandwidth: Bandwidth is always the scarce resource, so the mother

of the system design should be the available for bandwidth for operation. The

amount of bandwidth will play a significant role in determining number of

subcarriers, because with a large bandwidth, it is easily to be fit in large

number of subcarriers with reasonable guard space.

b. Required bit rate: The overall system should be able to support the data rate

required by the users. For example, to support broadband wireless multimedia

communication, the system should operate at more than 10 Mbps at least.

c. Tolerable delay spread: Tolerable delay spread will depend on the user

environment. Measurements show that indoor environment experiences

maximum delay spread of few hundreds of nanoseconds at most, whereas

outdoor environment can experience up to 10 μs. So the length of CP should

be determined according to the tolerable delay spread.

d. Doppler values: Users on a high speed vehicle will experience higher Doppler

shift where as pedestrians will experience smaller Doppler shift. These

considerations must be taken into account.

2.1.7 OFDM System Design Parameters

The design parameters are derived according to the system requirements. The

requirement of the system design must be fulfilled by the system parameters.

Following are the design parameters for an OFDM system (Van Nee and Prasad.

2000):

a. Number of subcarriers: Increasing number of subcarriers will reduce the data

rate via each subcarrier, which will make sure that the relative amount of

dispersion in time caused by multipath delay will be decreased. But when there

are large numbers of subcarriers, the synchronization at the receiver side will

be extremely difficult.

22

b. Guard time (CP interval) and symbol duration: A good ratio between the CP

interval and symbol duration should be found, so that all multipaths are

resolved and not significant amount of energy is lost due to CP. As a thumb

rule, the CP interval must be two to four times larger than the Root-Mean-

Square (RMS) delay spread. Symbol duration should be much larger than the

guard time to minimize the loss of SNR, but within reasonable amount. It

cannot be arbitrarily large, because larger symbol time means that more

subcarriers can fit within the symbol time. More subcarriers increase the signal

processing load at both the transmitter and receiver, increasing the cost and

complexity of the resulting device (Pollet et al. 1995).

c. Subcarrier spacing: Subcarrier spacing must be kept at a level so that

synchronization is achievable. This parameter will largely depend on available

bandwidth and the required number of subchannels.

d. Modulation type per subcarrier: This is trivial, because different modulation

scheme will give different performance (Rohling & May. 1997). For example

to improve the SER performance of OFDM system, it is better to use 64QAM

as mapping scheme than using 256QAM, whereas the system throughput will

be enhanced if 256QAM is used instead of 64QAM. Adaptive modulation and

bit loading may be needed depending on the performance requirement.

2.2 OFDM TRANSCEIVER SYSTEMS

An OFDM transceiver system is described in Figure 2.3. In this model, the input bits

are gathered together (1 for BPSK, 2 for 4-QAM, 4 for 16-QAM, etc.) and mapped to

corresponding constellation points. At this point, the data is represented in complex

numbers and they are in serial.

A serial to parallel converter is applied and the IFFT operation is performed on

the parallel complex data. The transformed data is grouped together again, as per the

number of required transmission subcarriers.

23

Cyclic prefix is inserted in every block of data according to the system

specification and the data is multiplexed to a serial fashion. At this point of time, the

data is OFDM modulated and ready to be transmitted. A Digital-to-Analog Converter

(DAC) is used to transform the time domain digital data to time domain analog data.

RF modulation is performed and the signal is up-converted to transmission frequency.

After the transmission of OFDM signal from the transmitter antenna, the

signals go through all the anomaly and hostility of wireless channel. After the

receiving the signal, the receiver down converts the signal; and converts to digital

domain using Analog-to-Digital Converter (ADC).

A block diagram of OFDM system model is given in Figure 2.1. A detailed

description of OFDM can be found in (Van Nee & Prasad 2000) where the expression

for one OFDM symbol starting at t= st can be found as follows:

Tttttts

TtttttT

ifjs

s sdts

ss

sssc

N

Ni

Ni

+>∧<=

+≤≤

−

+

−∑=−

−=+

, 0)(

, )(5.02exp Re)(

12

2

2π

(2.1)

where id are complex modulation symbols, sN is the number of sub-carriers, T the

symbol duration, and cf the carrier frequency.

The serial data symbols are converted to parallel data symbols which are fed to

the inverse fast Fourier transform (IFFT) block to obtain the time domain OFDM

symbols. Time domain samples are represented as:

( ){ }

10 ,2exp)(1

0−≤≤

=

=

∑−

=Nn

NnkjkX

kXIFFTxN

k

n

π (2.2)

24

Figure 2.1 OFDM system block diagram

Time domain signal is cyclically extended to avoid residual inter-symbol

interference (ISI) from the previous OFDM symbols. A simplified baseband digital

signal is converted to analog signal through the digital to analog converter (DAC)

block. Then, the signal is fed to the radio frequency (RF) front end. The RF front end

up-converts the signal to the RF frequencies using mixers, amplifies it using power

amplifiers (PA), and transmits it through antennas. In the receiver side, the received

signal is passed through a band-pass noise rejection filter and down-converted to

baseband by the RF front end.

The analog to digital converter (ADC) digitizes the analog signal and re-

samples it. After frequency and time synchronization (which are not shown in the

figure for simplicity), cyclic prefix (CP) is removed and the signal is transformed to

the frequency domain using the fast Fourier transform (FFT) block. A simplified

baseband model of the received symbols in the frequency domain can be written as:

X(k)

Data Out

Symbol Demod. P/

S

CP&ZP Remove

FFT

S/P

ADC RF Rx

Data In

Recovered data quality evaluation

Adaptive Modulation

S(t) X(k)

IFFT

S/P Symbol

Mod. DAC CP&ZP insertion P/

S Clipping

PA

Channel

AWGN

RF Tx

W(k)

H(k)

25

Y(k) = H(k)X(k) + W(k) (2.3)

where Y(k) is the received symbol on the kth subcarrier, H(k) is the frequency

response of the channel on the same subcarrier, and W(k) is the additive noise plus

interference sample which is usually assumed to be a Gaussian variable with zero

mean and variance of N0

/2. Note that OFDM converts the convolution in time domain

into multiplication in frequency domain, and hence simple one-tap frequency domain

equalizers can be used to recover the transmitted symbols.

After FFT, the symbols are demodulated, deinterleaved and decoded to obtain

the transmitted information bits. At the time of down-conversion of received signal,

carrier frequency synchronization is performed. After ADC conversion, symbol

timing synchronization is achieved. An FFT block is used to demodulate the OFDM

signal. After that, channel estimation is performed using the demodulated pilots.

Using the estimations, the complex received data is obtained which are demapped

according to the transmission constellation diagram. Finally, at this point the

originally transmitted bit stream is recovered.

2.2.1 OFDM Modulation and Demodulation

An excellent introduction to OFDM signal generation is given in (Popovic 1991) and

the presentation closely follows it.

The OFDM signal can (in general) be represented as the sum of N separately

modulated orthogonal sub-carriers as shown in Figure 2.2.

∑∑∞

−∞=

−

=

−=n

skkn

N

knTtgdts )()( ,

1

0

(2.4)

where 1,...,1,0),( −= Nktgk represent the N carriers and are given by

[ )stfj

k Ttetg k ,0 , )( 2 ∈= π (2.5)

26

In Equation (2.4), knd , stands for the symbol that modulates the kth carrier in

the nth signaling interval and each signaling interval is of duration Ts. From equation

(2.1), it is easy to note that N symbols are transmitted in Ts

time interval.

Figure 2.2 OFDM modulation block diagram

Source: Hazy 2004

The symbol sequence knd , is obtained by converting a serial symbol sequence

of rate N/Ts (symbol duration = Ts/N) into N parallel symbol sequences of rate 1/Ts

(each with symbol duration Ts

). As was mentioned previously, the sub-carrier

frequencies satisfy the following requirement:

1,...,2,1 , 0 −=+= NkTkff

sk (2.6)

where k is the carrier number, fo is the frequency of the carrier no.1, and Ts is

OFDM symbol duration. The signal transmitted in the nth signaling interval (of

duration Ts

) is defined as the nth OFDM frame, i.e.

∑−

=

−=1

0), ()(

N

kskknn nTtgdtF (2.7)

Transmitted OFDM signal

Total of N symbols

Total of k sub-carriers

27

Thus, the nth OFDM frame )(tFn consists of N symbols, each modulating

one of the N orthogonal sub-carriers. Since the carriers are orthogonal with each

other, it follows that the scalar product

[ ] ∫ −==sT

iksTdttigtkgsTtigtkg )()(*)()(),( δ (2.8)

Thus, the orthogonality of the carriers can be used to demodulate each of the

sub-carriers (without Inter-Carrier Interference) as follows:

∫+

=sTn

snTdttkgts

sTknd)1(

)()(1'. (2.9)

If there is zero Inter-Frame Interference, then the above expression reduces to:

∫+

==s

s

Tn

nTknkn

skn ddttgtF

Td

)1(

.'. )()(1 (2.10)

Thus, each sub-carrier in the transmitted signal and get back the transmitted

symbol sequence could be perfectly demodulated as shown in Figure 2.3.

Figure 2.3 OFDM demodulation block diagram

Source: Hazy 2004

Received OFDM signal

Total of N recovered symbols

28

2.2.2 QAM Mapping

Data on OFDM sub-carriers is mapped (modulated) using common digital modulation

schemes. The serial binary data is converted into complex numbers representing

constellation points and the constellation mappings usually Gray-coded. QAM is used

to generate a carrier modulated by all kinds of phase or phase/amplitude modulation

techniques. In such a system, the two-quadrature components of one carrier are

multiplied, each one with one datum taken in a finite set of data and are added to build

the modulated carrier every T seconds. In Figure 2.4 each pair of data (a, b,) can be

viewed as a point in a two-dimensional constellation that characterizes the

modulation. Generally and for practical reasons, the number of points in constellation

is a power of two. Let C be the number of points in a constellation:

C = 2a

The transmitted bit-rate is:

(2.11)

D = a/T bit/s (2.12)

Figure 2.4 QAM principle

Source: Hirosaki 1981

The performance of QAM in presence of additive Gaussian white noise

(AGWN) in the transmission channel depends on the distance between the points of

the constellation used (Proakis 1989). For a given energy per symbol and for a given

number of symbols, better results are obtained with constellations spread part. For

example 16-QAM performs better than 16-PSK.

29

In a QAM system, Figure 2.4, the two D/A converters deliver rectangular

pulses for each coordinate at the rate of 1/T pulse/s. The amplitude of these pulses is

equal to the coordinate of the current point to be transmitted. Consequently, the filters

have to be carefully designed to avoid impairment. An ideal lowpass filter with

impulse response has a sin x/x characteristic with zero-crossings for nTt ±= (n ≠ 0)

and a main-lobe peak at t = 0 has been introduced (Hirosaki 1981). To be optimum

with additive white Gaussian noise (AWGN) in the channel, the filtering operation is

equally shared between the transmitter and the receiver and generally the transmitted

signals are post-filtered by a x/sinx filter to cancel the influence of D/A converter

transfer function in the global channel impulse response. If ideal Nyquist filters are

used, the nominal bandwidth occupied by the modulated carrier is:

W = 1/T Hz. (2.13)

The nominal spectral efficiency of QAM is given by:

η = D/W = a bit/s/Hz, (2.14)

If (a) equals to 2 a constellation is used. In fact, ideal Nyquist filters do not

exist. In practice the Nyquist filters spectrum amplitude falls off more gradually.

Thus, these filters are characterized by a bandwidth excess or roll-off, α, that reflects

the loss in occupied bandwidth if compared with the nominal bandwidth.

Consequently, the spectral efficiency is reduced to:

η = a/(1 + α) (2.15)

Typical values for range from 0.2 to 0.5. All data carriers in one OFDM frame

are modulated using either QPSK, 16-QAM, 64-QAM, non-uniform 16-QAM or non-

uniform 64-QAM constellations. The constellations, and the details of the Gray

mapping applied to them, are illustrated in Figures 2.5, 2.6, and 2.7. The exact

proportions of the constellations depend on a parameter α, which can take the three

values 1, 2 or 4, thereby giving rise to the three diagrams in Figure 2.5 α is the

minimum distance separating two constellation points carrying different HP-bit values

divided by the minimum distance separating any two constellation points (ETSI

2008). Non-hierarchical transmission uses the same uniform constellation as the case

with α = 1. The exact values of the constellation points are z є {n + j m} with values

of n, m given below for the various constellations:

30

In 4-QAM, n є {-1, 1}, m є {-1, 1}

In 16-QAM with α = 1, n є {-3, -1, 1, 3}, m є {-3, -1, 1, 3}

In non-uniform 16-QAM with α = 2, n є {-4, -2, 2, 4}, m є {-4, -2, 2, 4}

In non-uniform 16-QAM with α = 4, n є {-6, -4, 4, 6}, m є {-6, -4, 4, 6}

In 64-QAM with α = 1, n є {-7, -5, -3, -1, 1, 3, 5, 7}, m є {-7, -5, -3, -1, 1, 3, 5, 7}

In non-uniform 64-QAM with α = 2, n є {-8, -6, -4, -2, 2, 4, 6, 8}, m є {-8, -6, -4, -2,

2, 4, 6, 8}

And in non-uniform 64-QAM with α = 4, n є {-10, -8, -6, -4, 4, 6, 8, 10}, m є {-10, -

8, -6, -4, 4, 6, 8, 10}.

(a) (b)

(c)

Figure 2.5 Constellation of different QAM schemes with α=1 (a) 4-QAM, (b) 16- QAM, (c) 64-QAM

Source: ETSI 2008

31

(a)

(b)

Figure 2.6 Constellation of different non uniform QAM schemes with α=2 (a) 16- QAM, (b) 64-QAM Source: ETSI 2008

(a)

32

(b)

Figure 2.7 Constellation of different non uniform QAM schemes with α=4 (a) 16- QAM, (b) 64-QAM

Source: ETSI 2008

2.2.3 OFDM Implementation by FFT

The number of sub-carriers N in OFDM systems is usually of the order of 100’s

implying that the transmitter and receiver blocks become bulky and expensive to

build. Also the oscillators (for generating the carrier frequencies) have temperature

instability and other problems (Weinstein & Ebert 1971). The Discrete Fourier

Transform is used to solve the modulation and demodulation complexities. The key

component in an OFDM transmitter is an inverse fast Fourier transform (IFFT) and in

the receiver, an FFT.

Figure 2.8 shows the implementation of IFFT/FFT in OFDM system. The

increasing computational power and performance capabilities of DSPs make them

ideal for the practical implementation of OFDM functions. Consumer products are

usually sensitive to cost and power consumption and for this reason, a fixed-point

DSP approach is preferred. However, fixed-point systems have limited dynamic

range, causing the related problems of round-off noise and arithmetic overflow. The

traditional approach to FFT design is to scale the signal so that overflow is avoided

(Robertson & Kaiser 1999).

33

Figure 2.8 OFDM implementation with IFFT/FFT

Source: Lee 2008

For OFDM systems using larger FFTs and fixed-point implementation, a large

word length is required if rounding errors are not going to significantly degrade

system performance. Scaling is usually distributed throughout the FFT structure as

this reduces the overall effect of rounding errors (Oppenheim & Schafer 1989). To

completely eliminate the possibility of overflow in a radix-2 implementation, numbers

must be scaled by a factor of one-half after each butterfly stage. Another way to avoid

overflow is to use Block Floating Point (BFP) scaling. This adapts the scaling at each

stage of the FFT according to the data, so that overflow does not occur for the given

input data. However, a single large signal sample can result in scaling which causes

large round off errors in all of the other signal values. To avoid this problem some

researchers have proposed a compromise method called convergent BFP, where

differing scaling factors are used for different sections of data (Lenart & Owall 2003).

In most applications, an Inverse Fast Fourier Transform is used, it performs the

transformation very efficiently, and provides a simple way of ensuring the carrier

signals produced are orthogonal. The IFFT performs, in one operation, the modulation

of each sub-carrier and the multiplexing of these sub-carriers.

34

The signal is then parallel-to-serial converted, converted to analog, and

modulated onto a high frequency carrier. At the receiver the signal is down converted,

converted to digital, and serial-to-parallel converted, before being input to the FFT.

The FFT performs demodulation and demultiplexing of each sub-carrier. The

distortion in the channel has the effect of changing the phase and amplitude of each

sub-carrier. This is corrected by the single tap equalizer.

The data is then input to the error decoder. The presence of the error decoder

means that the overall error rate does not depend on the noise in any one of the FFT

outputs, but on the statistics of the noise across all FFT outputs. This is closely related

to the ‘noise bucket’ effect, which has been observed for impulse noise in OFDM

(Suraweera & Armstron 2004).The FFT algorithm is based on a butterfly structure. It

has three stages. Each butterfly involves multiplication and addition. In the Matlab

simulations (MATLAB

Help. 2008), the structure in Figure 2.9 is used to model each

stage. Quantization was modeled only at the output of each stage. Infinite precision

was assumed within each stage. The signals within the IFFT and FFT in an OFDM

system are complex random variables.

Figure 2.9 Model of each FFT stage used in the Matlab simulations

Source: Lenart & Owall 2003

The effect of rounding and clipping depends on the probability distribution of

the signals throughout the FFT and IFFT structures. Figure 2.10 shows the

complementary cumulative distribution (CCD) for the real components at various

stages in the transmitter IFFT structure for a 64-point radix-2 transform and 4-QAM

inputs. No scaling is used, so the mean square (MS) values of the signals grow at each

stage as signals from the previous stages are summed.

35

Figure 2.10 CCD of real components within the IFFT structure

Source: Lenart & Owall 2003

2.2.4 Intersymbol and Intercarrier Interference

Most of wireless systems with multipath face the problem of intersymbol interference

(ISI). When the signal is transmitted from a transmitting antenna, it travels on

different paths to reach the receiving antenna. As the signal travels through different

path lengths, each signal arrives at the receiving antenna with a delay that is different

from other signals reaching the receiver. This leads to distortions in the received

signals. When the signal distortions take place due to previous signals, this results in

ISI.

There are other symbols as well involved in this system; hence ISI is not only

due to previous symbols but also to other symbols. There is interference between

symbols of the own carriers resulting in inter carrier interference (ICI) (Mishra 2010).

A well-known problem of such a multi-carrier modulation technique, however, is its

vulnerability to frequency-offset errors caused by oscillator inaccuracies and the

Doppler shift. In such situations, the orthogonality of the carriers is no longer

maintained, which results in ICI.

36

In other words ICI occurs when the multipath channel varies over one OFDM

symbol time (Bahai et al. 1999). When this happens, the Doppler shift on each

multipath component causes a frequency offset on the sub-carriers, resulting in the

loss of orthogonality among them. Finally, any offset between the sub-carrier

frequencies of the transmitter and receiver also introduces ICI to an OFDM symbol.

The orthogonality of sub-carriers can be viewed in either the time domain or

frequency domain. From the time domain perspective, each sub-carrier is a sinusoid

with an integer number of cycles within one FFT interval. From the frequency domain

perspective, this corresponds to each sub-carrier having the maximum value at its own

center frequency and zero at the center frequency of each of the other sub-carriers.

Figure 2.11a shows the spectra of four sub-carriers in the frequency domain for the

orthogonality case. The orthogonality of a sub-carrier with respect to other sub-

carriers is lost if the sub-carrier has nonzero spectral value at other sub-carrier

frequencies. From the time domain perspective, the corresponding sinusoid no longer

has an integer number of cycles within the FFT interval. Figure 2.11b shows the

spectra of four sub-carriers in the frequency domain when orthogonality is lost.

Researchers have proposed various methods to combat the ICI in OFDM systems. The

existing approaches that have been developed to reduce ICI can be categorized as

frequency-domain equalization (Al-Dhahir & Cioffi 1996; Jeon, et al. 2001), time-

domain windowing (Muschallik 1996), and the ICI self-cancellation (SC) scheme

(Zhao & Haggman 2001).

(a) (b)

Figure 2.11 Spectra of four (a) orthogonal and (b) non-Orthogonal sub-carriers

Source: Bing-Leung 2002

37

These methods give a higher signal-to-uncancelled-ICI ratio than standard

OFDM (Armstrong 1999). Several new schemes are also being exploited and

compared with existing methods.

2.2.5 Guard Time Insertion and Cyclic Extension

Guard Time is introduced in-order to eliminate the ISI almost completely. This is

done by making the guard time duration larger than that of the estimated delay spread

in the channel. If the guard period is left empty, the orthogonality of the sub-carriers

no longer holds, i.e., ICI comes into picture. In order to eliminate both the ISI as well

as the ICI, the OFDM symbol is cyclically extended into the guard period. Guard

interval was defined by an empty space between two OFDM symbols, which serves as

a buffer for the multipath reflection. The interval must be chosen as larger than the

expected maximum delay spread, such that multi path reflection from one symbol

would not interfere with another. In practice, the empty guard time introduces ICI.

ICI is crosstalk between different subcarriers, which means they are no longer

orthogonal to each other (Van Nee & Prasad 2000). A better solution was later found,

that is cyclic extension of OFDM symbol or CP. CP is a copy of the last part of

OFDM symbol which is appended to front the transmitted OFDM symbol (Matic

2001). CP still occupies the same time interval as guard period, but it ensures that the

delayed replicas of the OFDM symbols will always have a complete symbol within

the FFT interval (often referred as FFT window); this makes the transmitted signal

periodic.

For an OFDM transmitter with N sub-carriers, if the duration of a data symbol

is T’, the symbol duration of the OFDM symbol at the output of the transmitter is:

Ts

=T’ N (2.16)

where T’ is the duration of a data symbol and N is the total number of subcarriers.

38

Thus if the delay spread of a multipath channel is greater than T but less then

Ts

, the data symbol in the serial data stream will experience frequency-selective

fading while the data symbol on each sub-carrier will experience only flat-fading.

Figure 2.12 illustrates the concept of guard time insertion to eliminate ISI for

an OFDM symbol. In Figure 2.12a, an OFDM symbol received from the first path is

interfered by the previous OFDM symbol received from the second and third paths.

On the other hand, Figure 2.12b shows that the OFDM symbol received from the first

path is no longer interfered by the previous OFDM symbol. However, the received

symbol is still interfered by its replicas and this type of interference is referred as self-

interference.

Figure 2.12 Received OFDM symbols in a multipath channel (a) without guard time, (b) with guard time

Source: Bing-Leung 2002

39

If the delay spread is less than the guard time, the delay spread only introduces

a different phase shift for each sub-carrier but does not destroy the orthogonality

between sub-carriers. Guard time insertion can be performed in two ways:

a. Extract a portion of an OFDM symbol at the end and append it to the

beginning of the OFDM symbol. Samples after guard time insertion can be

expressed as:

)( GNkxgkx −+= , 0≤k≤N+G-1 (2.17)

where k is the sample index of an OFDM symbol, N is the number of subcarriers, G is

the guard time duration, and (k)N

is the residue modulo N .

b. Extract a portion of an OFDM symbol at the end and append it to the

beginning, and at the same time extract a portion of the OFDM symbol at

the beginning and append it to the end of the symbol. Samples after guard

time insertion can be expressed as:

NprefixTNkxgkx )( −+= , 0≤k≤N+G-1 , G=Tprefix+Tpost

(2.18)

where Tprefix is the guard time duration appending to the beginning of the symbol and

Tpost

is the guard time duration appending to the end of the symbol.

At the receiver side, CP is removed before any processing starts. As long as

the length of CP interval is larger than maximum expected delay spread τmax

SNR

, all

reflections of previous symbols are removed and orthogonality is restored. The

orthogonality is lost when the delay spread is larger than length of CP interval.

Inserting CP has its own cost, a part of signal energy is lost since it carries no

information. The loss is measured as

loss_cp= −10log10(1-TCP/Ts

)

(2.19)

40

Here, TCP is the interval length of CP and Ts

2.3 PEAK POWER PROBLEM

is the OFDM symbol duration. It

is understood that although part of signal energy is already lost, the fact that zero ICI

and ISI situation pay off the loss.

An OFDM signal has an approximately Gaussian amplitude distribution when the

number of subcarriers is large. Therefore, very high peaks in the transmitted signal

can occur. This property is often measured via the signal's PAPR.

2.3.1 PAPR of OFDM

Peak to Average Power Ratio (PAPR) is proportional to the number of sub-carriers

used for OFDM systems. An OFDM system with large number of sub-carriers will

thus have a very large PAPR when the sub-carriers add up coherently. Large PAPR of

a system makes the implementation of Digital-to-Analog Converter (DAC) and

Analog-to-Digital Converter (ADC) to be extremely difficult.

The design of RF amplifier also becomes increasingly difficult as the PAPR

increases. If the dynamic ranges of the A/D and D/A are increased, the resolution also

needs to be increased in order to maintain the same quantization noise level.

Therefore, an OFDM signal may require expensive A/Ds and D/As compared to many

other modulation formats.

Also, a large power back-off of the amplifiers is necessary. A major

disadvantage of an OFDM system is its large PAPR. As the number of sub-carriers N

increases, the maximum possible peak power becomes N times the average power (Li

& Cimini 1998).

2.3.2 Reasons for Reducing PAPR in OFDM

41

When the PAPR of an OFDM transmission is high, the D/A converters and power

amplifiers require a large dynamic range to avoid clipping of the given signal

mitigating undesirable consequences, such as signal distortion and spectral spillage.

Moreover, a large dynamic range implies increased complexity, reduced

efficiency and increased cost of the components. The reasons for reducing PAPR will

be elaborated in the following two sections.

a. Dynamic Range of D/A Converters and Power Amplifiers

Amplitude clipping of an OFDM signal causes several undesirable outcomes, such as

signal distortion and spectral regrowth (Li & Cimini 1998). It also causes in-band

noise, which results in SER performance degradation, and higher order harmonics that

spill over into out-of-band spectrum.

It has been shown that filtering after the power amplifier to remove this

spectral leakage is very inefficient with respect to power usage, thus making it an

undesirable solution (Krongold 2003). Therefore, the dynamic range of D/A

converters should be large enough to accommodate large peaks of signals, i.e. high

PAPR.

A high precision D/A converter supports high PAPR with reasonable

quantization noise, but may be very expensive for a given sampling rate of the system.

On the hand, low precision D/A converter would be cheaper, but quantization noise

will be significant which reduces signal SNR, when the dynamic range of the D/A

converter is increased to support high PAPR. Otherwise, the D/A converter will

saturate and clipping will occur (Tellado 2000).

Similarly, the dynamic range of the power amplifiers should also be large to

accommodate large PAPR. Otherwise, power amplifiers may saturate, resulting in

amplitude clipping. The component cost of the D/A converters and power amplifiers

increase in the dynamic range.

42

b. Power Savings

Power amplifiers with a high dynamic range exhibit poor efficiency, which is the ratio

of power delivered to the load and total power consumed.

For a given OFDM signal, the average input power needs to be adjusted such

that the peaks of the signal are rarely clipped. Therefore, the efficiency of the power

amplifiers is inversely proportional to the PAPR. Therefore, the net power savings is

directly proportional to the desired average output power and is highly dependent

upon the clipping probability level (Baxley & Zhou 2004).

2.3.3 PAPR Caculation in OFDM

An OFDM signal consists of a sum of independent signals modulated over several

orthogonal subcarriers of equal bandwidth. Therefore, when added up coherently, the

OFDM signal may exhibit large peaks, while the mean power remains relatively low.

Being a variant of OFDM signals suffer from this same problem.

By definition, the peak-to-average power ratio (PAPR) is the ratio of the peak

instantaneous power to the average power of a given signal, which characterizes the

envelope variations of the signal in time domain (Tellado 2000).

Recalling Equation (2.1), with Ns the number of subcarriers, di complex

modulation symbol, and s(t) one OFDM symbol starting at t=ts

, the PAPR formula is

given by:

{ }2

2

0

)(

)(max))(PAPR(

tsE

tsts Tt≤≤= (2.20)

where E{∙} denotes the expectation operator. Without loss of generality, the cyclic

extension can be neglected safely from analysis since it does not contribute to the

PAPR problem.

43

The continuous time PAPR of s(t) can be approximated using the discrete time

PAPR, which is obtained using samples of the OFDM signal s(n). It has been shown

that an oversampling factor of four is sufficient to estimate the continuous PAPR of a

BPSK system (Tellambura 2001; Yu & Wei 2003).

2.3.4 Distribution of PAPR

When the number of sub-carriers in an OFDM system is high, conventional OFDM

signals can be regarded as Gaussian noise like signals; their variable amplitude is

approximately Rayleigh distributed, and the power distribution has a cumulative

distribution function given by

F (z) = 1-e-z (2.21)

The probability that the PAPR is below some threshold is given by

P (PAPR ≤ z) = F (z)N = (1-e-z)N

(2.22)

where z is the Peak threshold value, and N is the total sub-carrier number. The

distribution is shown in Figure 2.13.

44

Figure 2.13 Cumulative distribution function of PAPR

Source: Hazy 2004

2.3.5 Effects of PAPR

The effects of the large Peak to Average Power ratio are:

a. The power amplifiers at the transmitter need to have a large linear range of

operation. When considering a system with a transmitting power amplifier, the

nonlinear distortions and peak amplitude limiting introduced by the High

Power amplifier (HPA) will produce inter-modulation between the different

carriers and introduce additional interference into the system. This additional

interference leads to an increase in the Symbol Error Rate (SER) of the system.

One way to avoid such non-linear distortion and keep low SER is by forcing

the amplifier to work in its linear region. Unfortunately such solution is not

power efficient and thus not suitable for wireless communication.

b. The Analog to Digital converters and Digital to Analog converters need to

have a wide dynamic range and this increases complexity.

2.4 PAPR Reduction Techniques

Numerous techniques have been proposed in the literature that attempt to reduce

PAPR of an OFDM signal. The PAPR can be reduced by amplitude clipping or

companding, by using a PAPR reduction code, by phase adjustments, or by precoding

(Du & Swamy 2010). These solutions include clipping and filtering (Li &

Cimini.1998), (Wang & Tellambura 2005), error control coding (Ahn et al. 2000),

(Jones et al. 1994), and constellation shaping techniques (phase, power, or both)

(Sezginer & Sari 2005; Krongold & Jones 2003; Han & Lee 2004).

The PAPR techniques can achieve a decrease in PAPR, but at the cost of

increased system complexity, reduced information rate, or degraded SER

45

performance. Moreover, due to non-contiguous subcarriers, the PAPR reduction

techniques proposed for the OFDM may need to be modified for reducing the values

of PAPR for OFDM signals.

Intentional or accidental clipping of the OFDM signal often occurs in practice.

The clipping of a received sample affects all subcarriers in the system. The sensitivity

to clipping effects is investigated by, e.g., (Gross & Veeneman 1993). At least three

concepts for reducing the peak-to-average power ratio have been proposed (Muller &

Huber, 1997; Narahashi & Nojima 1997; Jones & Wilkinson 1994; Van Nee 1996;

Tellado & Cioffi 1997). In the first concept one signal with a low peak-to-average

power ratio out of a set of signals is transmitted. In (Narahashi & Nojima

1997), for

instance, it is observed that by appropriately choosing the phase of each subcarrier the

peak-to-average power ratio can be reduced.

The second concept reduces the peak-to-average power ratio by coding. Block

codes can accomplish this, see, e.g., (Jones & Wilkinson 1994), and in (Van Nee

1996) it is shown that complementary codes have good properties to combine both

peak-to-average power reduction and forward error correction. Finally, in (Tellado &

Cioffi

1997) impulse-like time-domain functions are iteratively subtracted from the

original signal to reduce the peaks. These time-domain signals are generated by a set

of reserved, unused symbols in the DFT domain. Subcarriers which are not used to

transmit data symbols are used to transmit symbols, chosen to generate a transmitted

signal with low peak-to-average power ratio.

The PAPR reduction techniques broadly fall into one of the three techniques

(Sesia, et al. 2009):

a) Signal Distortion

b) Coding

c) Scrambling and Carrier selection

The proposed models in this thesis employed the clipping technique that fall

into the signal distortion techniques because of its simplicity and it happens at the

transmitter side. Moreover by a proper definition of the clipping level, the

46

improvement in the PAPR can be achieved without serious degradation in the SER

performance.

2.4.1 Clipping and Filtering Technique

Clipping is a way of reducing PAPR by very simply limiting the maximum amplitude

of the OFDM signal to a desirable maximum. Amplitude clipping limits the peak

envelope of the input signal to a predetermined value or otherwise passes the input

signal through unperturbed, that is, Then, the real valued bandpass samples, x, were

clipped at amplitude A as follows:

>≤≤

−<=

) (if )- (if

) (if -

AxAAxAx

AxAy (2.23)

where x denotes the signal before clipping and y denotes the signal after clipping.

This is clearly seen in Figure 2.14, where the clipping level is equal to 50 V.

When the OFDM peaks are greater than 50 or less than -50 V, the signal will be

clipped. Since the probability of the occurrence of the high peak power is low,

clipping is effective for reducing the PAPR.

47

2 4 6 8 10 12 14

x 10-7

-50

0

50

Time response of original signal

Time (sec)

Am

plitu

de (v

)

2 4 6 8 10 12 14

x 10-7

-50

0

50

Time response of clipped signal

Time (sec)

Am

plitu

de (v

)

Figure 2.14 Effects of clipping on OFDM signal

Figure 2.15 is illustrated the clipping and filtering technique. The distortion

caused by amplitude clipping can be viewed as another source of noise. The noise

caused by amplitude clipping falls in-band and out-of-band. In-band distortion cannot

be reduced by filtering and results in error performance degradation, while out-of-

band radiation reduces spectral efficiency.

Figure 2.15 Clipping and filtering

Source: Ergen 2009

x(t) y(t)

48

Filtering after clipping can reduce out-of-band radiation, but may also cause

some peak regrowth so that signal after clipping and filtering will exceed the clipping

level at some points. To reduce overall peak regrowth, a repeated clipping and

filtering operation can be used. Generally, repeated clipping and filtering takes many

iterations to reach a desired amplitude level. When repeated clipping and filtering is

used in conjunction with other PAPR reduction techniques described here, the

deleterious effects may be significantly reduced.

But clipping also has some disadvantages in the sense that it acts on the whole

of the signal instead of only on those points above threshold. This actually reduces the

SER. Definition of clipping level is very important issue and needs long observation

to the envelope of OFDM signal with different modulation schemes. The envelope of

OFDM signal has high fluctuation between low and high peaks. This fluctuation

increases as the order of the modulation scheme is increased. Fortunately the high

peaks in OFDM samples rarely happen.

This leads to necessity to implement simulation to observe the behavior of

OFDM sample and search for these high peaks. Finding these high peaks will ease the

mission of choosing the appropriate CR for each modulation scheme. In fact the

appropriate value of clipping ratio (CR) can be chosen based on other performance

metrics in OFDM system such as SER and SNR. The degree of clipping (hard or soft)

can affect on the value of SER, for example clipping OFDM signal at low CR will

cause serious degradation in SER.

The situation of channel decides the level of clipping that can be chosen. It is

better to use high CR at high SNRs and vice versa. Some moderate values of CR can

be use at high SNRs only because it offers reasonable SER performance. This leads to

necessity to perform classification of the values of CRs based on the order of

modulation schemes, calculated SER, and estimated SNR. With this classification the

clipping technique can offer compromise between PAPR improvement and reasonable

SER performance.

2.4.2 Significance of Clipping Technique

49

One of the limitations of using OFDM is the high peak-to-average power ratio (PAR)

of the transmitted signal. A large PAR leads to disadvantages such as increased

complexity of the analog to digital converter (A/D) and reduced efficiency of the radio

frequency (RF) amplifier. If power amplifiers are not operated with large linear-power

back-offs, it is impossible to keep the out-of-band power below imposed limits. This

leads to very inefficient amplification, expensive transmitters and causing

intermodulation among the subcarriers and undesired out-of-band radiation. The PAR

reduction techniques are therefore of great importance for OFDM systems.

Partial transmit sequences (PTS), selected mapping (SLM), active

constellation extension (ACE), Golay sequences and Reed-Muller codes (GRC),

clipping signal scheme, selective scrambling (SLS) and windowing signal scheme

were recently proposed to reduce PAR. The side information (SI) must be transmitted

to the receiver when using PTS, SLM and SLS methods, and then the channel

efficiency drops a little.

The complexity of using GRC method is too high to employ at real-time

practice, and it is only efficacious when the subcarrier number equals to several

special values as well. The ACE scheme wastes the precious power, especially when

the mobile’s power is very limited. The clipping signal scheme is relatively simpler

than others.

And the performance of the clipping scheme is superior to that of the

windowing signal scheme in OFDM systems, because the windowing technique

distorts all signals, but the clipping technique distorts small portion signal where the

peak power exceeds the max-permitted power. In this thesis the modulation selection

policy is combined with the clipping technique to produce an algorithm that can

improve the performance of OFDM based wireless systems in terms of PAPR, SER,

and data throughput.

When using the clipping scheme, the phase information of the signal is

completely transmitted, and the amplitude of the signal is clipped if the power of the

signal exceeds the max-permitted power (Dukhyun & Gordon 2007).

50

2.5 ADAPTIVE MODULATION

Current and future demands in wireless communication for various high speed

multimedia data services entail a robust, high data rate transmission system.

Increasing numbers of users amid limited spectrum motivate research on technology

to expand the capacity and increase spectral efficiency.

Adaptive modulation is a technique that varies some transmission parameters

to take advantage of favorable channel conditions. Under bad channel conditions, a

robust signal transmission mode will be applied to ensure reliable data exchange.

While, in good channel, spectrally efficient mode that offer higher throughput is

applied. In other words Adaptive Modulation (AM) is a technique used to provide

more user capacity over the air during good propagation conditions, where the

modulation level of the radio link adapts dynamically to the conditions of the path.

In traditional point to point systems the modulation is fixed at a certain level,

delivering a constant throughput for a defined channel bandwidth. This mechanism

ensures the most efficient mode is always used based on certain criteria and

constraints. The varying parameters can be the symbol transmission rate, transmitted

power level, constellation size, SER, code rate or scheme, any combination of these

parameters (Chung & Goldsmith 2001).

Compared to the fixed modulation system, which was designed specifically for

the worst case channel conditions, this adaptive modulation offers higher spectral

efficiency, higher throughput and remarkable capacity enhancement without

sacrificing SER or wasting power (Catreux et al. 2002). An early work includes in

(Webb & Hanzo 1994), where W.T. Webb and L. Hanzo introduced variable rate

QAM.

The transmitter varies the signal constellation size from 1bit/symbol

corresponding to BPSK to 6 bits/symbol star 64-QAM. In a good quality channel, the

constellation size is increased, and as the channel quality become worst, i.e. as the

51

receiver enters a deep fade, the constellation size is decreased to a value, which

provides an acceptable SER.

2.5.1 The Conventional Adaptive Modulation for OFDM

Adaptive Modulation in OFDM system refers to the automatic modulation adjustment

that OFDM based wireless system can make to prevent weather-related fading from

causing communication on the link to be disrupted. The goal of adaptive modulation is

to choose the appropriate modulation mode for transmission in each subcarrier, given

the local SNR γn

, in order to achieve a good tradeoff between throughput and overall

SER. The acceptable overall SER varies depending on other systems parameters, such

as the correction capability of the error correction coding and the nature of the service

supported by this particular link.

Figure 2.16 shows the concept of the adaptive modulation, this concept of the

selection policy states that a general estimate of the channel conditions needed for

different modulation schemes. When heavy weather conditions, such as a storm, affect

the transmission and receipt of data and voice over the wireless network, the radio

system automatically changes modulation so that non-real-time data-based

applications may be affected by signal degradation, but real-time applications will

continue to run uninterrupted. As the range is increased, it must be step down to lower

modulations (in other words, 16-QAM), but as the range get closer, it should be utilize

higher order modulations like 256-QAM for increased throughput.

Figure 2.16 The Conventional modulation selection policy

16-QAM 256-QAM 64-QAM

52

Since OFDM signals are modulated, varying the modulation also varies the

amount of bits that are transferred per signal thereby enabling higher throughputs and

better spectral efficiencies. For example, 256-QAM modulation scheme can deliver

approximately four times the throughput of 4-QAM. It should be noted, however as a

higher modulation technique is used, a better SNR is needed to overcome interference

and maintain a tolerable SER level. The problem arises in the conventional selection

policy when the channel conditions still the same for long time and the value of SNR

still without change (especially the low SNRs). This will reflect in a constant

throughput. Sometimes the transmitter receives wrong reading of the estimated SNR

and this means poor performance at all. As discussed before, the adaptive system has

to employ appropriate techniques in order to fulfill the following requirements:

− Channel quality estimation,

− Choice of the appropriate modulation modes, and

− Signalling or blind detection of the modulation modes.

2.5.2 Chanel Quality Estimation

It is well known that the wireless channel causes an arbitrary time dispersion,

attenuation, and phase shift in the received signal. The use of OFDM and a cyclic

prefix mitigates the effect of time dispersion. However, it is still necessary to remove

the amplitude and phase shift caused by the channel if you want to apply linear

modulation schemes. The function of channel estimation is to form an estimate of the

amplitude and phase shift caused by the wireless channel from the available pilot

information. The equalization removes the effect of the wireless channel and allows

subsequent symbol demodulation.

A number of different algorithms can be employed for these modules. This

application note considers simple techniques that illustrate the feasibility of

implementation and showcase the design methodology. Although the guard time

which has longer duration than the delay spread of a multipath channel can eliminate

ISI completely, the received symbol is still interfered by its replicas received from

multipath components.

53

This corresponds to frequency-selective fading of the symbol. In order to

compensate this distortion, a one-tap channel equalizer is needed for each sub-carrier.

At the output of FFT on the receiver side, the sample at each sub-carrier is multiplied

by the coefficient of the corresponding channel equalizer.

The coefficient of an equalizer can be calculated based on the zero-forcing

(ZF) criterion or the minimum mean-square error (MMSE) criterion (Sari, et al 1995).

The ZF criterion forces ISI to be zero at the sampling instant of each sub-carrier. The

coefficient of a one-tap ZF equalizer is calculated as follows:

nHnc 1= (2.24)

Where Hn is the channel frequency response within the bandwidth of the n-th

sub-carrier. The disadvantage of the ZF criterion is that it enhances noise at the n-th

sub-carrier if Hn

To make the tradeoff between ISI and noise, MMSE criterion is used and the

coefficient of a one-tap MMSE equalizer is calculated as follows:

is small, which corresponds to spectral nulls.

2

22

symbol

noisen

nn

H

Hc

σσ+

=∗

(2.25)

Where 2noiseσ is the noise variance and 2

symbolσ is the variance of source

symbols. A MMSE equalizer gives better performance than a ZF equalizer when

spectral nulls are present in the channel frequency response.

Equation 2.24 and 2.25 show that one needs to perform channel estimation in

order to obtain weights for equalizers on individual sub-carriers. Training symbols,

also known as pilot symbols, are also often used to perform channel estimation. In

OFDM, since equalization is performed in the frequency domain, it is the channel

frequency response that must be estimated. In the multipath environment, the

demodulated symbol Xn on the n-th subcarrier at the output of FFT without ISI and

ICI can be represented as:

54

( ){ } nn

L

lNnll

n NXjHY +

= ∑

−

=

1

0

2-exp)0( π (2.26)

Where L is the number of multipath components, Nn is the FFT of the additive

white Gaussian noise (AWGN) on the n-th subcarrier and Hl(0) is the channel

frequency response of the l-th multipath component at the zero-th frequency. To

estimate the channel frequency response, pilot symbols are inserted on the sub-carriers

in the frequency domain, i.e., they are inserted before IFFT operation at the

transmitter side. Let Hn be the channel frequency response experienced by Xn

, i.e.

∑−

=

=

1

0

2-exp)0(L

l

ln N

nljHH π (2.27)

The channel frequency response experienced by the pilot symbol P n

on the n

th subcarrier can be estimated as

n

nn

n

nn P

NH

PY

H +==∧

(2.28)

Since pilot symbols usually occupy a small amount of bandwidth n-th for

spectral efficiency, interpolation across frequency is required to estimate the channel

frequency response where pilot symbols are not located. The channel frequency

response at the m-th subcarrier mH∧

can be interpolated linearly as (Sampei & Sunaga.

1993)

∧∧∧

+

−= 211 pp H

NmH

NmH , p1≤m≤p2 (2.29)

Where 1pH∧

and 2pH∧

are the channel frequency responses estimated by the

pilot symbols on the p1-th and p2-th sub-carriers. Furthermore, if the multipath

channel is time-varying in nature, then interpolation across time may also require

tracking the channel. To determine the minimum pilot spacing in time and frequency

in OFDM, the bandwidth of the channel variation is necessary to be found in time and

frequency. These bandwidths are equal to the maximum Doppler frequency maxDf in

the time domain and the maximum delay spread maxτ in the frequency domain.

55

According to the sampling theorem, the pilot spacing in time ts and frequency fs is

(Hoeher, et al 1997).

sD

t Tfs

max2

1≤ (2.30)

F

s f ∆≤

max21

τ (2.31)

where sT is the OFDM symbol duration and F∆ is the frequency spacing between

two sub-carriers. Decreasing the pilot spacing improves the estimation of channel

frequency response but decreases bandwidth efficiency. On the other hand, increasing

the pilot spacing beyond the one specified by the sampling theorem decreases the

accuracy of the channel estimation but increases the bandwidth efficiency. Hence, the

chosen pilot density is a tradeoff between the performance of channel estimation and

bandwidth efficiency. Moreover, besides interpolating the channel frequency response

in the frequency and time domain separately, a two-dimensional interpolation can also

be applied in OFDM. More detail on the two-dimensional interpolation scheme can be

found in (Sari, et al 1995; Hoeher, et al 1997).

a. Channel Estimate Impact on Adaptive Modulation

In this section, the assumption of ideal channel knowledge will be removed that it was

held in the previous section. Here, the performance curves were found become even

more degraded. In the following plots, FFT channel estimation and SNR estimation

were incorporated into the system. The effectiveness of FFT estimation is based on the

pilot to information symbol ratio. There is a Nyquist condition that must be met

(Okamoto, et al. 1991).

Based on this criterion, the following relationship must be satisfied:

N

Tf sd 21. ≤ (2.32)

Where fd is the maximum Doppler frequency of the channel; Ts is the symbol period,

and N is the number of symbols in a frame and a frame is defined as a set of symbols

associated with a single pilot symbol.

56

The more pilots used per frame, the higher Doppler rate the estimator can

compensate for. In these simulations, one pilot was used per every fifteen information

symbols.

b. Propagation Delay Impact on Adaptive Modulation

Thus far, it was assumed that there has been no time lag or propagation delay when

the receiver relays control information back to the transmitter. In the system so far,

there has been instantaneous relay between receiver and transmitter. The delay will be

introduced in this system that will amount to two frames worth of time. In other

words, from the time the receiver transmits information back to the transmitter, two

more frames will be on route to the receiver from the transmitter and are not privy to

the latest information most recently sent from the receiver.

2.5.3 Choice of the Modulation Schemes

The two communicating stations use the open loop predicted channel transfer function

acquired from the most recent received OFDM symbol, in order to allocate the

appropriate modulation modes to the subcarriers. The modulation modes were chosen

from the set of BPSK, QPSK, and 16-QAM, as well as No Transmission, for which no

signal was transmitted.

These modulation modes are denoted by Mm

, where m ∈ (0, 1, 2, 4) is the

number of data bits associated with one data symbol of each mode. In order to keep

the system complexity low, the modulation mode is not varied on a subcarrier by

subcarrier basis, but instead the total OFDM bandwidth of 512 subcarriers is split into

blocks of adjacent subcarriers, referred to as subbands, and the same modulation

scheme is employed for all subcarriers of the same subband.

2.5.4 Conventional Modulation Selection Algorithm

57

a. Fixed Threshold Adaptation Algorithm

The fixed threshold algorithm was derived from the adaptation algorithm proposed by

Torrance for serial modems (Torrance, et al. 1999). In the case of a serial modem, the

channel quality is assumed to be constant for all symbols in the time slot, and hence

the channel has to be slowly varying, in order to allow accurate channel quality

prediction.

Under these circumstances, all data symbols in the transmit time slot employ

the same modulation mode, chosen according to the predicted SNR. The SNR

thresholds for a given long term target SER were determined by Powell optimization

(Torrance & Hanzo 1996).

Torrance assumed two uncoded target bit error rates: 1% for a high data rate

(speech) system, and 10−4 for a higher integrity, lower data rate (data) system. The

resulting SNR thresholds ℓn for activating a given modulation mode Mm in a slowly

Rayleigh fading narrow band channel for both systems are given in Table 2.5.

Specifically, the modulation mode Mm is selected if the instantaneous channel SNR

exceeds the switching level ℓn

.

Table 2.5 Optimized switching levels for adaptive modulation for the (speech) and (data) system, shown in instantaneous channel SNR (dB)

System type ℓ ℓ0 ℓ1 ℓ2

Speech

3

-∞ 3.31 6.48 11.61

58

Data -∞ 7.98 10.42 16.76

Source: Torrance & Hanzo 1996

This adaptation algorithm originally assumed a constant instantaneous SNR

over all of the block’s symbols, but in the case of an OFDM system in a frequency

selective channel the channel quality varies across the different subcarriers. For sub–

band adaptive OFDM transmission, this implies that if the subband width is wider

than the channel’s coherence bandwidth (Webb & Hanzo 1994). Then the original

switching algorithm cannot be employed. For these investigations, therefore it is

essential to employ the lowest quality subcarrier in the subband for the adaptation

algorithm based on the thresholds given in Table 2.5.

b. Sub-band BER Estimator Adaptation Algorithm

As was seen in previous section, the fixed switching level based algorithm leads to a

throughput performance penalty, if used in a subband adaptive OFDM modem, when

the channel quality is not constant throughout each subband. This is due to the

conservative adaptation based on the subcarrier experiencing the most hostile channel

in each subband.

An alternative scheme taking into account the nonconstant SNR values γj

across the Ns subcarriers in the j-th subband can be devised by calculating the

expected overall bit error probability for all available modulation modes Mn

in each

subband. For each subband, the mode having the highest throughput, whose estimated

BER is lower than a given threshold, is then chosen.

While the adaptation granularity is still limited to the subband width, the

channel quality estimation includes not only the lowest quality subcarrier, which leads

59

to an improved throughput. It can be seen that the BER estimator algorithm results in

significantly higher throughput, while meeting the BER requirements. The BER

estimator algorithm is readily adjustable to different target bit error rates. Such

adjustability is beneficial, when combining adaptive modulation with channel coding.

Table 2.6 lists a brief comparison between the most known conventional

modulation selection algorithms in AM. The two proposed models in this thesis

suggest other performance metrics such as SER and CR to be used together with SNR

to select the appropriate modulation technique among the utilized modulation

schemes.

AMCl algorithm in both models presents new modulation selection policy in

order to improve the PAPR, enhance the data throughput and maintains a reasonable

error level in OFDM based wireless systems. This policy tries to avoid the

disadvantages of the conventional selection policies of Torrance and Hanzo.

Table 2.6 Conventional modulation selection algorithms in AM

Modulation selection algorithm

Properties Disadvantages

Fixed threshold adaptation (Torrance Model)

1. The channel quality is assumed to be constant for all symbols in the time slot.

2. All data symbols in the transmit time slot employ the same modulation mode.

3. Modes are chosen according to the predicted SNR.

4. The SNR thresholds for a

given long term target SER were determined by Powell optimization.

1. It assumes a constant instantaneous SNR over all of the block’s symbols, but in OFDM system in a frequency selective channel the channel quality varies across the different subcarriers.

2. If the subband width is wider than the channel’s coherence bandwidth. Then the original switching algorithm cannot be employed.

3. The fixed switching level

based algorithm leads to a throughput performance penalty, if used in a sub-band adaptive OFDM modem.

60

Subband BER estimator adaptation (Hanzo Model)

1. The expected overall bit error probability is calculated for all available modulation modes in each subband.

2. The mode having the highest throughput, whose estimated BER is lower than a given threshold, is then chosen.

3. The BER estimator algorithm results in significantly higher throughput, while meeting the BER requirements.

4. The BER estimator algorithm is readily adjustable to different target bit error rates.

5. The adjustability is beneficial, when combining adaptive modulation with channel coding.

1. Delay that comes from the calculation process of the quality of the received OFDM signal. This delay increases as the order of modulation mode increases.

2. This algorithm should employs channel coding technique to maintain the error level under the target value, this leads to overhead in the transmitted data.

3. Due to the inverse relation between BER and PAPR, thus this algorithm cannot offer low peak powers performance in OFDM system.

2.5.5 Signaling and Blind Detection

The adaptive OFDM receiver has to be informed of the modulation modes used for the

different sub-bands. This information can either be conveyed using signaling

subcarriers in the OFDM symbol itself or the receiver can employ blind detection

techniques in order to estimate the transmitted symbols’ modulation modes.

a. Signaling

The simplest way of signaling the modulation mode employed in a sub–band is to

replace one data symbol by an M-PSK symbol, where M is the number of possible

modulation modes. In this case, reception of each of the constellation points directly

signals a particular modulation mode in the current sub-band. In this case, for four

modulation modes, and assuming perfect phase recovery, the probability of a

signaling error ps(γ), when employing one signaling symbol is the symbol error

probability of QPSK. Then the correct sub-band mode signaling probability is:

61

( )( ) ( )( )2,11 γγ QPSKbpsp −=− (2.33)

where pb, QPSK is the bit error probability for QPSK:

( ) ( )

==

2erfc.

21, λγγ QQPSKbp (2.34)

which leads to the expression for the modulation mode signaling error probability of

( )2

2erfc.

2111

−−=

γγsp (2.35)

The modem mode signaling error probability can be reduced by employing

multiple signaling symbols and maximum ratio combining of the received signaling

symbols Rs,n, in order to generate the decision variable R's

prior to decision:

*,.

1,' nsH

sN

nnsRR

∑=

= (2.36)

where Ns is the number of signaling symbols per sub-band, the quantities Rs,n

nsH ,ˆ

are the

received symbols in the signaling subcarriers, and represents the estimated

values of the frequency domain channel transfer function at the signaling subcarriers.

Assuming perfect channel estimation and constant values of the channel transfer

function across the group of signaling subcarriers, the signaling error probability for

Ns

signaling symbols can be expressed as:

( )2

2 erfc.

2111,'

−−=

γγ sNsNsp (2.37)

b. Blind Detection by SNR Estimation

The receiver has no a prior knowledge of the modulation mode employed in a

particular received sub–band and estimates this parameter by quantizing the de–faded

received data symbols nn HR ˆ in the sub–band to the closest symbol mnR ,ˆ for all

62

possible modulation modes Mm for each subcarrier index n in the current subband.

The decision directed error energy em

for each modulation mode is calculated

according to:

( )2,ˆ∑ −=

nmnnnm RHRe (2.38)

The modulation mode Mm which minimizes em

is chosen for the demodulation

of the sub-band. It can be seen that the detection performance depends on the number

of symbols per sub-band, with fewer sub-bands and therefore longer symbol

sequences per sub–band leading to a better detection performance. It is apparent,

however, that the number of available modulation modes has a more significant effect

on the detection reliability than the block length.

If all four legitimate modem modes are employed, then reliable detection of

the modulation mode is only guaranteed for AWGN SNR values of more than 15-18

dB, depending on the number of sub-bands per OFDM symbol. If only M0 and M1

are

employed, however, the estimation accuracy is dramatically improved. In this case,

AWGN SNR values above 5-7 dB are sufficient to ensure reliable detection.

c. Blind Detection by Multi-mode Trellis Decoder

If error correction coding is invoked in the system, then the channel decoder can be

employed to estimate the most likely modulation mode per sub–band. Since the

number of bits per OFDM symbol is varying in this adaptive scheme, and the channel

encoder’s block length therefore is not constant, for the sake of implementational

convenience a convolutional encoder at the transmitter must be chosen.

Once the modulation modes to be used are decided upon at the transmitter, the

convolutional encoder is employed to generate a zero–terminated code–word having

the length of the OFDM symbol’s capacity. This codeword is modulated on the

subcarriers according to the different modulation modes for the different sub–bands,

and the OFDM symbol is transmitted over the channel. At the receiver, each received

63

data subcarrier is demodulated by all possible demodulators, and the resulting hard

decision bits are fed into parallel trellises for Viterbi decoding.

2.5.6 Adaptation Benefits

The fundamental idea in AM is to shift to a lower modulation when the link budget of

a system is no longer sufficient, typically during a rain fade. This modulation shift

results in an improved link budget (receiver threshold is improved and transmit power

can be increased), allowing the system to still operate, but at a lower throughput. In

order for this to be valuable, the microwave system must be able to perform priority

queuing on the user traffic.

By engineering a network with adaptive modulation, the operator can perform

several optimizations. For an existing operator with an existing network and frequency

licenses, the operator can use adaptive modulation to get much more throughput out of

the existing channels. For example, a channel of 28 MHz may have only been

engineered to 16QAM before, with about 80 Mbps throughput, but with adaptive

modulation, could now run at 256QAM during regular operation at close to 200 Mbps.

This can enable a two to three times capacity increase without having to

acquire additional or new licenses, or change antenna sizes. For a new deployment,

adaptive modulation can be used to minimize the antenna sizes of the link, while still

being able to transport high capacities. This will reduce antenna equipment costs, as

well as installation costs. More significantly, this will also reduce ongoing tower lease

costs, which are a significant portion of operating costs for many service providers.

Alternatively, in a new deployment, adaptive modulation may used to optimize

spectrum usage, and minimize annual frequency lease costs. This is especially

significant in Europe, where spectrum costs are quite high.

2.5.7 Adaptation Boundaries

Adaptive modulation is a powerful technique for maximizing the data throughput of

subcarriers allocated to a user. Adaptive modulation involves measuring the SNR of

64

each subcarrier in the transmission, then selecting a modulation scheme that will

maximize the spectral efficiency, while maintaining an acceptable SER. Adaptive

modulation is utilized to take advantage in the randomness of the channel. When the

channel is in good condition, the transmission is performed with higher data rates, and

when the channel is poor, the transmission rate is lowered with small constellation and

low rate codes. The channel side information is feeded to transmitter in order to

control transmit power, transmit constellation, and the coding rate (Ergen 2009).

Using adaptive modulation in a wireless environment is much more difficult as

the channel response and SNR can change very rapidly, requiring frequent updates to

track these changes. Adaptive modulation in wireless environment has not been used

extensively (Kim et al. 2004; Wong et al. 1999; Falahati et al. 2004; Tang & stolpman

2004), since the channel response and SNR can change very rapidly, and requires

frequent updates to track these changes. In 1999 Wong and Cheng investigated the

effectiveness using an adaptive subcarrier, bit and power allocation and use of

adaptive modulation and adaptive user allocation reduced the transmit power by 10 dB

(Zhang 2004; Shen et al. 2003).

It is important to know how to change the modulation scheme. In other words,

there is need to a way for the system to decide which modulation scheme is best suited

for the present conditions. Pons and Dunlop (1998) claimed that SER at the receiver

would be a good channel metric to decide switching. However, the decision was made

to use the metric that Pons and Dunlop rejected, which is to estimate the SNR of the

link. Reliable SER estimation is difficult over short periods and thus would restrict

adaptation rate. Therefore the selection policy in the adaptive modulation is based on

the estimated SNR. In other words the best modulation scheme will be selected based

on the estimated SNR. The SNR threshold can be defined based on the AWGN

performance of each modulation scheme. SNR can be defined as the signal power

divided by noise power. This resultant signal power is the instantaneous received

signal power and can be compared directly to the noise power, thus allowing the

system to consider the SER in an AWGN channel. From Torrance and Hanzo (1996)

the probability of bit error of QPSK, 16QAM, and 64QAM as follows:

65

)()( γγ QQPSKP = (2.39)

+

+

=

5213

5541)(16

γγγγ QQQQAMP (2.40)

−

+

+

−

−

+

+

+

+

+

+

+

+

+

=

13119

753

753

75364

21121

21121

2161

2161

2141

2141

2131

21121

21121

2161

2161

21212121121)(

γγγ

γγγγ

γγγγ

γγγγγ

QQQ

QQQQ

QQQQ

QQQQP QAM

(2.41)

In Equations 2.39 – 2.41, γ is the SNR, and Q(.) is the Q function,

dxexQx

x

∫=∞ −

2

2

21)(π

(2.42)

Refer to Table 2.7 and at an operating SER of 10-3

(as example) there is no

modulation scheme that gives the desired performance at an SNR below 10dB.

Therefore, QPSK was chosen as it is the most robust.

Table 2.7 AWGN switching thresholds

Modulation scheme SNR Threshold

QPSK (4-QAM) SNR < 17 dB

16-QAM 17 dB ≥ SNR ≥ 23 dB

64-QAM SNR > 23 dB

Source: Chan 2003

2.5.8 Limitations of Adaptive Modulation

66

There are several limitations with adaptive modulation. Overhead information needs

to be transferred, as both the transmitter and receiver must know what modulation is

currently being used. Also as the mobility of the remote station is increased, the

adaptive modulation process requires regular updates, further increasing the overhead.

There is a tradeoff between power control and adaptive modulation. If a remote station

has a good channel path the transmitted power can be maintained and a high

modulation scheme used (i.e. 64-QAM), or the power can be reduced and the

modulation scheme reduced accordingly (i.e. QPSK). Distortion, frequency error and

the maximum allowable power variation between users limit the maximum

modulation scheme that can be used. The received power for neighboring subcarriers

must have no more than 20 - 30 dB variation at the base station, as large variations can

result in strong signals swamping weaker subcarriers. Inter-modulation distortion

results from any non-linear components in the transmission, and causes a higher noise

floor in the transmission band, limiting the maximum SNR to typically 30 - 60 dB.

Frequency errors in the transmission due to synchronization errors and Doppler shift

result in a loss of orthogonality between the subcarriers. A frequency offset of only 1-

2 % of the subcarrier spacing results in the effective SNR being limited to 20 dB

(Moose 1994). Moreover the limited SNR restricts the throughput of the system.

The problem in the conventional policy is the system throughput at low SNRs.

In other words, the best modulation scheme should be selected based on SNR, this

means the system throughput will be kept constant as long as the channel conditions

does not change. This is because each modulation scheme is assigned to a group of

SNRs called SNR thresholds. Therefore if the estimated value of SNR is located

within the boundaries of one group, OFDM system will utilize only one particular

modulation scheme.

Another problem when wrong estimated value of SNR is received and this

problem can be worse if this wrong value of SNR is low. All these problems lead to

constant throughput for specific period of transmission time. The long observation of

the received OFDM signal shows the possibility of happen a sudden improvement in

SER even the transmitter still receiving the same SNR or value belongs to the same

group. This means that the system loses chance to change the order of modulation

scheme for some subcarriers that offer SER.

67

Unfortunately this leads to degradation in the data throughput of OFDM

system. It is better to use another performance metrics to make decision about the

order of modulation scheme in AM instead of SNR. This thesis will present models of

modulation selection policies that can offer huge enhancement in the system

throughput and introduce a compromise between the two important performance

metrics that are SER and PAPR.

2.5.9 Theoretical Performance of Adaptive Modulation

It is essential to discuss the theoretical performance of adaptive modulation, both in

terms of SER and spectral efficiency, and refer to Torrance and Hanzo (Torrance &

Hanzo 1996) for an analysis of adaptive modulation. First, PDF of the fluctuations of

the received, instantaneous, Rayleigh amplitude, s should be defined.

The envelope of a Rayleigh fading channel has a distribution of:

( )Ss-exp2),(S

sSsF = (2.43)

where, S is the average signal power. Next, it is necessary to determine the SER of

each modulation scheme. The SER can be determined analytically by:

dsSsFNsP

NSP G ),().()(

0∫=∞

γ (2.44)

where Pγ is the Rayleigh channel SER, and PRGR is the SER performance in an AWGN

channel. With the above two equations in addition to Equations 2.39-2.41, it is easy to

find the SER performance of adaptive modulation as:

68

∫+

∫+

∫

= −

dsSsFNsP

dsSsFNsP

dsSsFNsP

BNSP

l

lQAM

l

lQAM

l

lQPSK

A

),().(4

36

),().(3

24

),().(2

12

.)(

64

161 (2.45)

where the li are the SNR thresholds between the modulation schemes and B is the

average spectral efficiency. The values of li

can be inferred from Table 2.5. The value

of B is computed as follows:

∫ ∫ ∫++=2

1

3

2

4

3),(.6),(.4),(.2

l

l

l

l

l

ldsSsFdsSsFdsSsFB (2.46)

Having established the mathematical foundation behind adaptive modulation,

it is better to investigate the results in graphical form.

2.5.10 Parameters Adaptation

Different transmission parameters can be adapted to the anticipated channel

conditions, such as the modulation and coding modes.

Adapting the number of modulation levels in response to the anticipated local

SNR encountered in each subcarrier can be employed, in order to achieve a wide

range of different tradeoffs between the received data integrity and throughput.

Corrupted subcarriers can be excluded from data transmission and left blank or used

for example for Crest–factor reduction. A range of different algorithms for selecting

the appropriate modulation modes are investigated below. The adaptive channel

coding parameters entail code rate, adaptive interleaving and puncturing for

convolutional and turbo codes, or varying block lengths for block codes (Webb &

Hanzo 1994). Based on the estimated frequency–domain channel transfer function,

spectral predistortion at the transmitter of one or both communicating stations can be

invoked, in order to partially of fully counteract the frequency–selective fading of the

69

time dispersive channel. Unlike frequency-domain equalization at the receiver, which

corrects for the amplitude and phase errors inflicted upon the subcarriers by the

channel but cannot improve the SNR in poor quality channels spectral predistortion at

the OFDM transmitter can deliver near constant signal-to- noise levels for all

subcarriers and can be thought of as power control on a subcarrier-by-subcarrier basis.

In addition to improving the system’s SER performance in time dispersive

channels, spectral predistortion can be employed in order to perform all channel

estimation and equalization functions at only one of the two communicating duplex

stations. Low cost, low power consumption mobile stations can communicate with a

base station that performs the channel estimation and frequency domain equalization

of the uplink, and uses the estimated channel transfer function for pre–distorting the

downlink OFDM symbol. This setup would lead to different overall channel quality

on the uplink and downlink, and the superior downlink channel quality could be

exploited by using a computationally less complex channel decoder having weaker

error correction capabilities in the mobile station than in the base station. If the

channel’s frequency–domain transfer function is to be fully counteracted by the

spectral pre-distortion upon adapting the subcarrier power to the inverse of the

channel transfer function, then the output power of the transmitter can become

excessive, if heavily faded subcarriers are present in the system’s frequency range.

In order to limit the transmitter’s maximal output power, hybrid channel pre–

distortion and adaptive modulation schemes can be devised, which would deactivate

transmission in deeply faded subchannels, while retaining the benefits of pre-

distortion in the remaining subcarriers.

a. Signaling the Parameters

Signaling plays an important role in adaptive systems and the range of signaling

options is summarized in Figure 2.17 for both open loop and closed loop signaling, as

well as for blind detection. If the channel quality estimation and parameter adaptation

have been performed at the transmitter of a particular link, based on open loop

adaptation, then the resulting set of parameters has to be communicated to the receiver

70

in order to successfully demodulate and decode the OFDM symbol. If the receiver

itself determines the requested parameter set to be used by the remote transmitter the

closed loop scenario then the same amount of information has to be transported to the

remote transmitter in the reverse link. If this signaling information is corrupted, then

the receiver is generally unable to correctly decode the OFDM symbol corresponding

to the incorrect signaling information.

Unlike adaptive serial systems, which employ the same set of parameters for

all data symbols in a transmission packet (Torrance, et al 1999), adaptive OFDM

systems have to react to the frequency selective nature of the channel, by adapting the

modem parameters across the subcarriers. The resulting signaling overhead may

become significantly higher than that for serial modems, and can be prohibitive for

example for subcarrier-by-subcarrier modulation mode adaptation. In order to

overcome these limitations, efficient and reliable signaling techniques have to be

employed for practical implementation of adaptive OFDM modems. If some

flexibility in choosing the transmission parameters is sacrificed in an adaptation

scheme, like in the sub–band adaptive OFDM schemes described below, then the

amount of signaling can be reduced. Alternatively, blind parameter detection schemes

can be devised, which require little or no signaling information, respectively.

(a) Reciprocal channel, open-loop control

Signal modem modes used by BS

Downlink (DL)

Uplink (UL) MS

Evaluate perceived channel quality and

decide the transmission mode of local TX

BS

Evaluate perceived channel quality and

decide the transmission mode of local TX

Signal modem modes used by MS

Uplink (UL)

Downlink (DL)

Signal modem modes to be used by BS

MS

Evaluate perceived channel quality and

signal the requested the transmission mode to

the BS TX

BS

Evaluate perceived channel quality and

signal the requested the transmission mode of

the MS TX

71

(b) Non-reciprocal channel, closed-loop signalling

(c) Reciprocal channel, blind modem-mode detection

Figure 2.17 Signaling scenarios in adaptive modems

Source: Torrance, et al. 1999

2.5.11 Constant Throughput Adaptive OFDM

The time varying data throughput of an adaptive OFDM modem operating with either

of the two adaptation algorithms discussed above makes it difficult to employ such a

scheme in a variety of constant rate applications. Torrance (Torrance, et al 1999)

studied the system implications of variable throughput adaptive modems in the

context of narrowband channels, stressing the importance of data buffering at the

transmitter, in order to accommodate the variable data rate. The required length of the

buffer is related to the Doppler frequency of the channel, and a slowly varying

channel as required for adaptive modulation results in slowly varying data throughput

and therefore the need for a high buffer capacity.

Uplink (UL)

No signaling

No signaling

Downlink (DL)

MS - Evaluate perceived channel quality and decide the transmission mode of local TX. - Infer the BS TX’s transmission mode blindly.

BS - Evaluate perceived channel quality and decide the transmission mode of local TX. - Infer the MS TX’s transmission mode blindly.

72

Real time interactive audio or video transmission is sensitive to delays, and

therefore different modem mode adaptation algorithms are needed for such

applications. The constant throughput AOFDM scheme proposed here exploits the

frequency selectivity of the channel, while offering a constant bit rate. Again, subband

adaptivity is assumed, in order to simplify the signaling or the associated blind

detection of the modem schemes. The modulation mode allocation of the subbands is

performed on the basis of a cost function to be introduced below, based on the

expected number of bit errors in each subband.

The expected number of bit errors, en,s, for each subband n and for each

possible modulation mode index s, is calculated on the basis of the estimated channel

transfer function, taking into account also the number of bits transmitted per subband

and per modulation mode, bn,s. Each subband is assigned a state variable sn holding

the index of a modulation mode. Each state variable is initialized to the lowest order

modulation mode, which in this case is 0 for no transmission. A set of cost values cn,s

is calculated for each subband n and state s as follows:

snsn

snsnsn bb

eec

,1,

,1,, −

−=

+

+ (2.47)

For all but the highest modulation mode index s. This cost value is related to

the expected increase in the number of bit errors, divided by the increase of

throughput, if the modulation mode having the next higher index is used instead of

index s in subband n. In other words, Equation 2.47 quantifies the expected

incremental bit error rate of the state transition s converges to s + 1 in subband n.

The modulation mode adaptation is performed by repeatedly searching for the

block n having the lowest value of cn, sn and incrementing its state sn

. This is repeated

until the total number of bits in the OFDM symbol reaches the target number of bits.

Because of the granularity in bit numbers introduced by the subbands, the total

number of bits may exceed the target. In this case, the data is padded with dummy bits

for transmission.

73

2.6 SUMMARY

This chapter presents the fundamentals of OFDM theory necessary for reading this

thesis

. It reviews the evolution of OFDM system and some OFDM based wireless

system that will be used in this thesis to verify the proposed selection policy models

and recovery method. OFDM important issues, requirement, and parameters are

reviewed and discussed in details.

In this chapter, the block diagram of OFDM transceiver system is presented.

Each component in this system is reviewed and explained with more details such as

modulation/demodulation process, mapping process, zero padding and cyclic prefix

insertion. In addition this chapter presents

the literature studies done on two important

issues in OFDM system namely PAPR and AM. Definition and distribution of PAPR

is reviewed and the simplest PAPR reduction technique that is clipping and filtering is

presented in this chapter. The benefits and limitation of AM are discussed in details.

Some critics and recommendations regarding clipping and AM techniques are

presented in this chapter.

CHAPTER III

METHODOLOGY

3.1 INTRODUCTION

In recent years adaptive modulation has emerged as a popular technique to improve

data throughput and system capacity in a wireless system. The basic idea is to adapt

the modulation scheme to the channel quality, using different schemes for different

channel conditions. Therefore one primary issue is to determine the selection policy or

switching thresholds between the modulation schemes.

The conventional selection

policy utilize only one modulation scheme at each SNR. The higher order modulation

schemes needs high SNR to avoid any degradation in the system performance. In

other words the low order schemes are utilized at low SNRs, whereas the higher

schemes can be utilized at high SNRs.

In addition this conventional policy classifies the values of SNR into number

of groups called boundaries or thresholds. The boundaries of each group define the

limits that each modulation scheme can work within in order to offer error rate under

the target level. This means that the data throughput of OFDM system is kept low at

low SNRs. In addition because of each modulation scheme is assigned to group of

SNRs, the data throughput will be kept constant at these SNRs. Moreover the problem

in this conventional policy arises when the bad channel condition still without change

for specific period of time, because this will keep the system throughput low and

constant.

74

Another problem can be faced if the transmitter receives wrong estimation

about the value of SNR. The effects of this wrong estimation can be worse if the

received SNR is low. It is found by long observation of the quality of the received

OFDM signal that the calculated SER shows some improvement despite the

transmitter still receives the same estimated SNR.

This scenario could be happened when group of users are located in the same

area. The subcarriers that are dedicated to these users will be modulated using the

same modulation scheme because the estimated SNR is the same in all subcarriers.

Despite the location of some users could be changed inside the area due to their

movement toward the base station; it is found that the transmitter still receives the

same SNR or SNRs that belong to thresholds of one particular modulation scheme,

whereas the calculated SER shows sudden improvement. This leads to necessity of

suggestion other performance metrics to be used in the modulation selection policy.

These problems cause degradation in the throughput and the spectral efficiency

of OFDM system. Improving the spectral efficiency of OFDM signal is not the

important issue, OFDM suffers from another serious problem that is called PAPR.

Many applications relay on OFDM to provide them with high data transmission, and

this leads to necessity of utilizing high order modulation schemes in mapping process

of OFDM system. Utilizing high order scheme such as 256-QAM in OFDM increases

the PAPR. This increment in PAPR becomes higher in OFDM applications that utilize

large number of subcarriers. The simplest PAPR reduction technique is clipping the

high peaks of OFDM signal.

This chapter describes the methodology used to improve the performance of

the OFDM by improving the performance of the adaptive modulation (AM) and

clipping techniques. These improvements include proposing two models of

modulation selection policy that is controlled by clipping technique through careful

selection of the clipping ratio (CR) for each utilized modulation scheme. In addition,

this chapter will describe the clipped signal recovery method that is proposed to

eliminate the effect of the clipping technique on the SER performance of the OFDM

system.

75

3.2 VERIFIED SYSTEMS

It is essential to study the effects of the proposed improvement in the adaptive

modulation and clipping technique on various OFDM applications. The verified

systems in this simulation are as follows:

1. IEEE 802.11g.

2. IEEE 802.16e.

3. DVB-T.

4. Fourth Generation (In general).

Table 3.1 shows the parameters of the verified systems. It is essential to

investigate the improvement in the PAPR, SER, and throughput of each tested system

after applying the new form of AM and propose a solution to mitigate the effects of

the clipping technique on the SER performance. This is because of each tested system

has different number of subcarriers and this difference will reflect into the response of

each system to these proposed improvements.

Fourth generation is among the verified systems, because it relies on the

OFDM system to be its multiple access technology and provide it with the required

high data rates. The spectral efficiency of 3G networks is too low to support high data

rate services at low cost. As a consequence one of the main focuses of 4G systems

will be to significantly improve the spectral efficiency. So it is essential and important

to investigate the effects of the proposed improvements in the adaptive modulation

and the clipping technique on the overall performance of the 4G system especially the

throughput of the system.

The proposed models of modulation selection can provide data rates begin

from 125 Mbps (when using BPSK as a modulation technique) to 1 Gbps (when using

256-QAM as a modulation technique) which meets the requirements of the 4G

system. Also the other tested systems show a good response to the proposed

improvements and the overall performance of them were improved.

76

Table 3.1 Simulation parameters of verified systems

Parameters

System

DVB-T IEEE

802.16e

Fourth

generation

IEEE

802.11g

Modulation schemes

(Mapping schemes)

BPSK, 4-QAM, 16-QAM, 64QAM, 128-QAM,

256-QAM

IFFT size (2N-IFFT) 4096 2048 512 128

Number of data subcarriers 1705 720 128 48

Useful symbol duration TU 224

(μs) 91.43 1.02 4

Channel bandwidth (MHz) 7.61 10 125 20

Carrier frequency (GHz) 0.09 2.24 2.5 2.4

Carrier spacing (1/ TU 4.46 ) (KHz) 10.94 980.39 250

Allowed guard interval G 1/8 1/8 1/4 1/5

Guard Time ( Tg =G ×TU 28 ) (μs) 11.43 0.25 0.80

The reasons that stand behind choosing the above mentioned OFDM based

wireless systems are listed in Table 3.2. Identifying a compromise between reasonable

SER performance and low peak to average power ratio is the most important issue in

OFDM systems.

Moreover providing users with high data rate is the needed most in the current

and future communications technologies. Most wireless systems rely on OFDM to

provide them with high data rate transmission, reduction gain in PAPR, and maintain

an accepted error rate at all SNRs.

77

Table 3.2 Desired requirements of the verified systems

OFDM system Desired requirements IEEE 802.11g

An 802.11G signal has a short range and is susceptible to

interference from other access point, microwave ovens, and cordless

phones. Moreover 802.11g should support users with a maximum

rated speed of 54 Mbps. Thus, OFDM with a good performance of

SER and high spectral efficiency is needed to meet all these

requirements.

IEEE 802.16e OFDM with adaptive modulation (AM) can enable IEEE 802.16e

technology to support peak DL data rates up to 63 Mbps in a 10

MHz channel. IEEE 802.16e employs a large number of subcarriers

(2048), Therefore high PAPR is such system. In addition the line of

sight is needed for longer connection. Thus, IEEE 802.16e has

smaller cell size than GSM and CDMA technologies.

DVB-T DVB-T utilizes very large number of subcarriers up to 32K

(32×1024). Thus, it suffers from high PAPR. DVB-T employs

OFDM with adaptive modulation and coding (AMC) to support

maximum achievable throughput rate of 72 Mbps in 8 MHz channel.

4G (in general) Fourth generation technologies rely on OFDM to provide users with

nominal high data rate of 100 Mbps

while the client physically

moves at high speeds relative to the station, and 1 Gbps while client

and station are in relatively fixed positions. In addition, Peak power

problem should not be existed in 4G technologies.

3.3 CALCULATION OF OFDM PARAMETERS

For a given bit rate R and the delay spread of a multipath channel τ, the parameters of

an OFDM system can be determined as follows (Van Nee & Prasad 2000):

78

a) As a rule of thumb, the guard time G should be at least twice the delay

spread, i.e.

τ2≥G (3.1) where τ is delay spread and G is the guard interval. To minimize the signal-to-noise

ratio (SNR) loss due to the guard time, the symbol duration should be much larger

than the guard time. However, symbols with long duration are susceptible to Doppler

spread, phase noise, and frequency offset. As a rule of thumb, the OFDM symbol

duration Ts

should be at least five times the guard time, i.e

GTs 5≥ (3.2)

b) The frequency spacing between two adjacent sub-carriers ∆f is

sT

f 1=∆ (3.3)

c) For a given data rate R, the number of information bits per OFDM symbol

info B is

so RTB =inf (3.4)

d) For a given Binfo and the number of bits per symbol per sub-carrier Rsub

number of sub-carriers N is

, the

sub

o

RB

N inf= (3.5)

where Rsub is 2 bits/symbol/sub-carrier for QPSK, Rsub

is 4 bits/symbol/sub-carrier

for 16-QAM. The OFDM bandwidth signal is defined as

fNBW ∆= (3.6)

Two observations are made from the above calculations:

a. Increasing the symbol duration decreases the frequency spacing between sub-

carriers. Thus, for a given signal bandwidth, more sub-carriers can be

accommodated. On the other hand, for a given number of sub-carriers,

increasing the symbol duration decreases the signal bandwidth.

79

b. Increasing the number of sub-carriers increases the number of samples per

OFDM symbol. However, it does not necessary imply that the symbol duration

increases. If the OFDM symbol duration remains the same, the duration

between two samples decreases as a result. This implies the increase in the

OFDM signal bandwidth. On the other hand, if the OFDM signal bandwidth is

fixed, then increasing the number of sub-carriers decreases the frequency

spacing between two sub-carriers, which in turn increases the symbol duration.

The duration between two samples remain the same in this case.

3.3.1 Oversampling

The PAPR of a continuous-time OFDM signal cannot be computed accurately by

sampling the signal at Nyquist rate. Oversampling should be used to overcome this

problem. Oversampling means using a sampling rate, which is greater than the nyquist

rate. Neither sampling theory nor quantizing theory require oversampling to be used to

obtain a given signal quality, but Nyquist rate conversion places extremely high

demands on component accuracy when a converter is implemented. Oversampling

allows a given signal quality to be reached without requiring very close tolerance, and

therefore expensive components (Watkinson 2001).

Although it can be used alone the advantage of oversampling are better realized when

it is used in conjunction with noise shaping. When calculating the PAPR, the actual

time domain signal has to be considered that is in analog form. The IFFT outputs,

which are symbol spaced sampling values, will miss some of the signal peaks. If

PAPR is calculated by using these sample values, then the calculated PAPR is less

than the actual PAPR. This is an optimistic result and will not illustrate the real

situation. However, they are enough for signal reconstruction. To account for this

issue, oversampling is performed by low pass filtering the IFFT signal and then

sampled at a higher rate. Now, the increased samples are close to the real analog

signal and calculation of PAPR based on these samples will give the true PAPR.

80

There is about 3dB difference in maximum PAPR when it is measured without

oversampling and with oversampling by a factor of four. It is good enough to make

oversampling by a factor of four and further increase in oversampling will not make

much difference.

3.3.2 Zero Padding

All standard OFDM systems are based on a cyclic prefix (CP) to eliminate inter-block

interference (IBI) between successive blocks. A CP of length no less than the channel

order is inserted per transmitted block. Discarding the CP at the receiver not only

suppresses IBI, but also converts the linear channel convolution into a circular one,

which facilitates the diagonalization of the channel matrix, and makes single-tap

equalization using scalar division possible.

An obvious problem in CP-OFDM systems is that the transmitted symbols

cannot be recovered when some channel zeros are located on sub-carriers. Recently, it

has been proposed in (Wang & Giannakis 2000), to replace CP insertion by zero

padding (ZP) at the end of the block of symbols to be transmitted. The padded zeros

deterministically suppress the IBI but lead to a larger number of observed samples.

That way, the transmitted symbols can always be retrieved regardless of the channel

zero locations (Van Nee & Prasad 2000). Note that since the number of zeros required

to cancel IBI equals the CP length, ZP-OFDM and CP-OFDM transmission have the

same bandwidth (BW) efficiency. In OFDM-DVB-T system the total number of zeros

that should be added to the OFDM symbol can be calculated using the following

equation:

ZP = NFFT – Nsub

= 4096 – 1705

(3.7)

= 2391 zeros

where ZP is the total no. of padded zeros, NFFT is the total no. of FFT points, and Nsub

is the total no. of subcarriers.

81

This means 2391 zeros are added to the OFDM symbol to achieve

oversampling and to centre the spectrum. The other advantages of ZP are that the FFT

algorithm becomes faster if the time domain vector size is a power of 2

and the power

consumption can be reduced.

3.3.3 Implementation Complexity Reduction

The uniform bandpass sampling theorem has been modified to cope with sampling

frequency instability and carrier frequency variations.

This technique is widely used in

a variety of applications, such as radar, communication, optics, etc. In radar and EW

(Electronic Warfare) applications, it is generally necessary to translate the received

bandpass signal into baseband inphase and quadrature (denated by I and Q)

components.

In this case, the amplitude and phase relationship between the I and Q

components carries the desired information, it is convenient to express the bandpass

signal in the complex form as follows:

tofifjetm

tofifjetjQtI

tQjxtIxtx

)(2)(

)(2)]()([

)()()(

−=

−+=

+=

π

π (3.8)

Where m(t) is low-pass complex signal, which has a two-sided bandwidth B

such that the signal spectrum M(f) = 0, for | f | ≥ B/2. Digital sampling technique can

obtain much better balance between I and Q channel than analog technique does.

Several direct digital quadrature sampling methods have been presented, but

those methods require that a special position relationship must be satisfied between

the input carrier frequency and its bandwidth or A/D sampling rate, and cannot

process arbitrary carrier frequency bandpass signal (Yunsong et al. 1999

).

82

The carrier frequency of bandpass signal is generally unknown, its estimated

value could be only obtained. Using the method based on the bandpass signal

complex, the modulated complex envelope of bandpass signal (denoted by XI(n) and

XQ

(n)) within baseband sampling rate can be produced, also when the carrier

frequency is equal to 1/4 A/D sampling rate, the output of I and Q channel is exactly

equal to the I and Q component of a bandpass signal.

In order to reduce the implementation complexity in the constructed system

the complex-valued baseband OFDM signal is modulated up to a carrier frequency

equal to 1/4 of the sampling frequency.

3.3.4 2N-IFFT

The first task to consider is that the OFDM spectrum is centered on fc; i.e., the first

subcarrier is (N-1)/2Tu MHz to the left of the carrier and the last subcarrier is (N-

1)/2Tu MHz to the right, where Tu

is the useful duration of OFDM symbol and N is

the total number of subcarriers.

One simple way to achieve the centering is to use a 2N-IFFT and T/2 as the

elementary period, where T is the elementary period (Van Nee & Prasad 2000).

3.4 THE CLIPPING RATIO

Selection of initial clipping ratio (CR) depends on the signal constellation being used.

It is important to observe, that the samples of the discrete time OFDM signal can

exhibit large peaks. The peaks are larger for higher order modulation schemes than for

lower order schemes.

For the case of OFDM-4QAM, it is known that the highest peak is equal to the

total number of subcarriers being used. In the case of OFDM with 16QAM, 64-QAM,

128QAM, and 256-QAM, the highest peak can be greater than the number of

subcarriers.

83

Therefore, by selecting a suitable clipping level and a proper phase an

amplitude correction factor significant PAPR reduction is achieved without causing

significant SER degradation. This is a desired feature in portable devices in WLANs,

where power efficient transmitter power amplifiers are essential. To study the effect of

clipping on PAPR a Clipping Ratio (CR), defined as the ratio of clipping level to the

root mean square (RMS) value of OFDM symbol power, is used.

A clipping ratio of 1 would mean that clipping is done at the RMS value and a

clipping ratio of 2 would mean that clipping is done at twice the RMS value. In a

clipped OFDM system, the required dynamic range is determined by the clipping

ratio. The following tradeoff with regard to the clipping ratio emerges: a low clipping

ratio causes signal distortion and decreases capacity (Ochiai, Imai 2002). However, it

also increases the power efficiency of the power amplifier (Antognetti 1986), which

increases capacity. Recalling equation (2.23), where y is the clipped signal and A is

the clipping level. The clipping ratio (CR) is defined as (Li and Cimini 1998)

σA

= CR (3.9)

And the clipping ratio in dB is given by:

[ ] σAlog20CR dB = (3.10)

where σ is the root mean squared (RMS) power of the unclipped OFDM signal, and its

mathematical expression is

( )∑==

N

kts

N 1

22 1σ (3.11)

It can be easily shown that, for an OFDM signal with N subchannels, N=σ

for a baseband signal and 2N=σ for a bandpass signal. For example, for an

OFDM signal with 128 subchannels, 128=σ for a baseband signal and

82128 ==σ for a bandpass signal. Therefore, CR =1 is equivalent to A= 8,

meaning that signal is clipped at the RMS power level. The CR of 0.8 means the

clipping level is about 2 dB lower than RMS level and a CR of 1.4 means the clipping

level is about 3 dB higher than RMS level.

84

The definition of CR is essential to get the advantage of clipping technique.

Unfortunately clipping OFDM signal leads to discards high peaks; therefore all data in

these peaks will be lost. This leads to face in-band distortion that causes serious

degradation in SER. To make compromise between achieving improvement in PAPR

and maintain the SER performance under an accepted value is an important issue.

Most of researches classify clipping technique as distortion technique that causes

degradation in SER. However clipping is the most effectiveness PAPR reduction

technique because of its simplicity and by defining appropriate value of CR, better

PAPR improvement can be achieved without causing serious degradation in SER. It is

important to note that the definition of CR relays on two performance metrics that are

SER and SNR.

Clipping OFDM signal at low CR causes degradation in SER. Therefore the

values of CRs must be defines based on the target SER in each OFDM system. The

channel condition affect on the definition of CR, for example at low SNRs OFDM

signal encounters bad condition that causes losing in the data. Therefore, clip OFDM

signal at such SNRs leads to serious degradation in the quality of the received signal.

Some value of CRs cannot be used at low SNRs, whereas clip OFDM signal with

these CRs at high SNRs offer reasonable SER performance. In other words to get the

advantage of clipping technique, the CR should be defined based on the estimated

value of SNR. In fact the values of CR can be classified into three categories based on

the channel condition or SER namely low, moderate and high. Such classification will

improve the functionality of clipping technique to be able to offer improvement in

PAPR without causing serious degradation in SER.

3.5 COMPLEMENTARY CUMULATIVE DISTRIBUTION FUNCTION

The Complementary cumulative distribution function (CCDF) of the PAPR denotes

the probability of an OFDM signal exceeds a given threshold (Tellado 2000). It is the

most frequently used parameters to characterize PAPR and also as performance

measures for PAPR reduction techniques.

85

In the literature, it is customary to use the CCDF of the PAPR as a

performance criterion. The CCDF of the PAPR is defined as the probability that the

PAPR per OFDM symbol exceeds a certain clipping level PAPR0.

CCDF(PAPR(x)) = Prob(PAPR(x) > PAPR0) (3.12)

CCDF curves provide critical information about the signals encountered in 3G

systems. These curves also provide the peak-to-average power data needed by

component designers. This application note examines the main factors that affect

power CCDF curves, and describes how CCDF curves are used to help design systems

and components. Figure 3.1 shows the power versus time plot of OFDM signal. This

plot represents the instantaneous envelope power defined by the equation:

Power = I2 + Q2 (3.13)

Where I and Q are the in-phase and quadrature components of the waveform.

Unfortunately, the signal in the form shown in Figure 3.1 is difficult to quantify

because of its inherent randomness and inconsistencies. In order to extract useful

information from this noise-like signal, a statistical description of the power levels in

this signal is needed, and a CCDF curve gives just that.

Figure 3.1 Construction of a CCDF curve

Source: Agilent 2000

Ref -10 dBm RF envelope

1

0

Avg

1

2

3

Time

Amplitude

86

A CCDF curve shows how much time the signal spends at or above a given

power level. The power level is expressed in dB relative to the average power. Figure

3.2 displays the CCDF curve of the OFDM signal. Here, the X-axis is scaled to dB

above the average signal power, which means the peak-to-average ratios are actually

measured as opposed to absolute power levels. The Y-axis is the percent of time the

signal spends at or above the power level specified by the X-axis.

For example, at t = 1% on the Y-axis, the corresponding peak-to-average ratio

is 7.5 dB on the X-axis. This means the signal power exceeds the average by at least

7.5 dB for 1 percent of the time. The position of the CCDF curve indicates the degree

of peak-to-average deviation, with more stressful signals further to the right.

Now that a practical CCDF curve has been shown in Figure 3.2, the

mathematics of CCDF curves will be investigated briefly. To obtain the Cumulative

Distribution Function (CDF), the integral of the PDF should be computed. Finally,

inverting the CDF results in the CCDF. That is, the CCDF is the complement of the

CDF (CCDF = 1 – CDF).

Figure 3.2 CCDF curve of a typical OFDM signal

Source: Agilent 2000

0

3

2

1

15 X-axis is dB above average power

The signal power exceeds the average by at least 7.5 dB for 1% of

the time

Band-limited Gaussian noise CCDF reference

line

Y-axis is the percent of the time the signal power is at or above the power specified by the X-axis

100%

1%

0.1%

10%

0. 010%

0.0010%

0.00010%

87

Figure 3.3 shows the power CCDF curves of both a 16-QAM and QPSK

signal. It is easy to verify that the 16-QAM signal has a more stressful CCDF curve

than that of the QPSK signal. While 16-QAM is capable of transmitting more bits per

state than QPSK for a given symbol rate, it also produces greater peak-to-average

ratios than does QPSK.

Figure 3.3 CCDF curves of a 4QAM signal and a 16-QAM signal

Source: Agilent 2000

3.6 SIGNAL TO NOISE RATIO

The SNR can be found by finding the ratio between the signal power and the noise

power. These powers must be averaged over multiple symbols to smooth out the

variations in the noise. For a typical fixed wireless system, the amplitude of the signal

will vary because of either multipath fading or rain fading events.

Since the noise power level from the receiving equipment is constant, the SNR

will vary as the signal level fades. The relevant parameter, then, is the instantaneous

SNR rather than the average SNR.

15

16-QAM signal

QPSK signal 100%

1%

0.1%

10%

0.010%

0.0010%

0.00010% PAPR (dB)

Prob

abili

ty

88

The error rate then because a variable that follows the fading. When the signal

level fades to a low level, the error rate rises during that fade, potentially resulting in

an error burst that can destroy a block of data, or system synchronization, and timing.

(dB) 2

log10log10SNR0

2

100

10

=

=

NV

NEb (3.14)

Where Eb is the energy used to transmit a single information bit, N0

V

is the single-sided

noise power spectrum density, and is the average voltage of the signal modulation

constellation. Recall the variance noise in AWGN is

oN 2 =σ (3.15)

Then The SNR is equal to

(dB) 2

log20SNR

=

σV (3.16)

3.7 ERROR VECTOR MAGNITUDE

EVM is a metric of modulation quality that has become a standard measurement in a

number of different digital radio technologies, particularly those using some variant of

QAM (Alexander 2007). It is generally used to assess the transmitter signal quality

and determine the degree of signal impairment (i.e. deviation from the ideal expected

signal). Figure 3.4 defines EVN and several terms. As shown in this figure, EVM is

the scalar distance between the two phasor end points, i.e., it is the magnitude of the

difference vector. Expressed another way, it is the residual noise and distortion

remaining after an ideal version of the signal has been stripped away. The principle

underlying the EVM measurement is as follows. QAM modulation consists of a series

of complex number that are used to modulate a high frequency carrier by altering its

amplitude and phase. The ideal modulated transmit signal can be represented as a set

of constellation points on a 2-D complex plane, with the real and imaginary values of

the signal falling along the X and Y axes, respectively.

89

Then, as shown in Figure 3.4, the errors in the transmitted signal can be

represented as vector deviations from these points. Essentially, the impaired

transmitted signal can be represented as vector deviations from these points.

Essentially, the impaired transmitted signal at any time instant can be considered as

the vector sum of an ideal signal and an error signal.

The EVM result is defined as the square root of the ratio of the mean error

vector power to the mean reference signal power expressed as a percentage.

Mathematically, the error vector e can be written as

e = y – x (3.17)

where y is the modified measured signal and x the ideal transmitted signal. EVM can

be defined as

[ ][ ]2

2

rms

EVM

xEeE

= (3.18)

The EVM measurement reconstructs the digital data by demodulating the

transmitted signal, maps the digital data to the ideal constellation points, and then

subtracts (vectorially) these ideal points from the actual measured constellation points.

The process of subtraction yields the error that was introduced during the modulation

process.

The error vectors calculated for each modulation symbol from the EVM

measurement process are then averaged on an RMS basis over some defined length of

data (e.g., 1000 symbols, or even an entire frame) and then expressed as a percentage;

this is the EVM. Note that only the absolute magnitude of the error vectors are taken,

the phase of the error vector is not relevant to the EVM measurement. A 100% EVM

indicates that all of the constellation points of the transmitted signal have shifted or

smeared into other constellation points, and the original signal cannot be successfully

recovered because no constellation point can be distinguished from another. (In fact,

complex modulation schemes such as 64-QAM are completely uncoverable with as

little as 35% EVM).

90

On the other hand, a 0% EVM indicates that the transmitted signal exactly

matches the ideal, which is, of course, impossible. (The EVM is therefore also

equivalent to the relative constellation error of the modulated signal).

Figure 3.4 Measurement of EVM

Source: Alexander 2007

3.8 SYMBOL ERROR RATE

Symbol Rate refers to the number of symbols that are transmitted in one second. From

the symbol rate, one can calculate the bandwidth (total number of bits per second) by

multiplying the bits per symbol times the symbol rate, or it is an indication of the

speed at which the signal is transmitted.

Ideal (reference) constellation point

Error vector

Error vector magnitude (EVM)

Magnitude error (I/Q error magnitude)

Phase error (I/Q error phase)

Actual (measured) constellation point

I

Q

0

0

91

In other words, the number of symbols transmitted per second and expressed

in baud (for example, 1 Mbaud = 1,000,000 symbols per second). The error rate can

be defined as the measurement of the effectiveness of a communications channel. It is

the ratio of the number of erroneous units of data to the total number of units of data

transmitted.

The error, which is a symbol error, is calculated by comparing the original

constellation with the one that is outputted by the M-QAM slicer. The theoretical

probability of symbol error for rectangular QAM constellation is given in (Proakis &

Salehi 2000) as follows:

−

−=

−−=

o

avM

MM

NMEQ

MP

PP

).1(.3.112

where,

)1(1 2

(3.19)

where Eav is the average energy per bit; M = 2k

represents the number of levels and k

is the number of bits per symbol. Equation (3.58) is for the case of k even. For k odd,

there is no exact result. However, the symbol-error probability is upper bounded as:

−≤

o

avM NM

EkQP

).1( 3

4 (3.20)

The value of k can be defined according to the selected modulation scheme to

map the input data, for example k=2 when the modulation scheme is 4-QAM. The

formulas for the symbol error probability for BPSK can be found as follows:

=

o

avM N

EP erfc

21 (3.21)

92

3.9 THE PROPOSED ADAPTIVE MODULATION SELECTION MODELS

In order to solve the problems in conventional modulation selection policy of AM that

were discussed early in Chapters I and II, two models of modulation selection are

proposed as shown in Table 3.3 namely mode (1) and model (2). Each model offers

numerous of tested modes that in turn employ different order of modulation schemes.

Model (1) includes eight modes that employ five, four, or three modulation

schemes, whereas model (2) includes only two modes that employ five and four

modulation schemes.

Table 3.3 The proposed models and modes of modulation selection policy

Model Proposed modes Utilized modulation schemes Note

Model

(1)

Mode (A) 4+16+64+128+256-QAM policy is

SER

controlled

Utilization

percentage in

both models

is controlled

by the

clipping ratio

(CR)

Mode (B) 4+16+64+256-QAM

Mode (C) 4+16+64-QAM

Mode (F) BPSK+4+16+128+256-QAM

Mode (G) BPSK+4+16+64+256-QAM

Mode (H) BPSK+4+16+64-QAM

Mode (I) BPSK+16+64-QAM

Model

(2)

Mode (D) 4+16+64+128+256-QAM Policy is

SNR and

SER

controlled Mode (E) 4+16+64+256-QAM

93

The selection policy in each model is combined with the clipping technique to

produce an algorithm called Adaptive Modulation and Clipping (AMCl). This

algorithm will try to take the advantage of the two combined techniques. It aims to

reduce PAPR, enhance the system throughput, and offers reasonable SER. The SER

performance that should be achieved depends on the tested mode. In other words, in

the modes those utilize high modulation schemes such as 128-QAM and 256-QAM;

AMCl algorithm should offer SER better than normal OFDM with the same schemes.

Modulation selection policy in AM is proposed in both models. This policy in

model (1) is controlled by the SER. In other words the modulation schemes are

utilized in the mapping process based on the SER of last symbol transmission. All

available modulation schemes are utilized especially at low SNRs. As the SNR is

increased, AMCl algorithm discards the low order modulation schemes. The

modulation selection policy in model (2) is controlled by SNR and SER. The SNR and

SER value will be used to decide which modulation schemes must be selected. In this

model one or two modulation schemes as maximum could be selected at each SNR.

In both models the utilization percentage of the modulation schemes are

controlled by appropriate definition of the clipping ratio (CR). In model (1), AMCl

employs updating mechanism of the clipping level for each modulation scheme at

each new symbol transmission. The boundaries of CR of each scheme depend on the

estimated SNR. The utilization percentage in model (2) is also controlled by CR;

however only two values of CR of each modulation scheme are defined based on the

target SER value.

3.10 THE PROPOSED SYSTEM MODELS

Figure 3.5 shows the proposed system of models (1) and (2) in OFDM system. The

symbol modulator decides which modulation scheme should be chosen to map the

input data based on the SER value only as in model (1), or based on the values of both

SNR and SER as proposed in model (2).

94

There is a feedback path from the receiver to the transmitter for sending values

of SER and SNR that represent the situation of channel and quality of received signal.

The tested modes in each model will be selected based on the situation of the channel;

therefore the system will be able to decide which mode should be chosen to meet the

channel quality requirement.

Some modes employ high order modulation schemes such as 256-QAM and

128-QAM, therefore it is essential to select the modes with low order modulation

schemes if the channel quality is very poor.

Figure 3.5 OFDM block diagram with the proposed modulation selection policy in AMCl

Each proposed model offers possibility to utilize more than one modulation

scheme at each SNR. The modulation selection policy in the two proposed models

chooses the best order based on some performance metrics such as SER, and SNR.

AW

GN

cha

nnel

Cyclic Prefix

Remove

Symbol Mod.

Cyclic Prefix

Insertion

DAC

Symbol Demod. ADC

PA

Data sink

Clipping

Data Source

RF

Tx IFFT

RF Rx

FFT

Modulation schemes

adaptation

Clipping ratio

updating mechanism

SER calculation

Mode selection

Modulation selection policy in AMCl

SNR Estimation

95

The values of these metrics are calculated after each successful symbol

transmission. AMCl algorithm with each model will define the utilization percentage

of each modulation scheme using updating mechanism of the CR.

The value of CR depends on the order of utilized modulation scheme. This

mechanism is different in each proposed model in terms of definition the boundaries

or thresholds of CR. In model (1) it depends on the SNR thresholds of each

modulation scheme, whereas in model (2) it depends on the target value of SER. The

AMCl algorithm in the two models will be discussed in details in the next sections.

3.10.1 The Algorithm AMCl in Model (1)

The modulation selection policy in model (1) is controlled by SER. In other words the

modulation schemes are utilized in the mapping process based on the SER that is

calculated in last OFDM symbol transmission. At low SNRs, AMCl in model (1)

utilizes all available modulation schemes to map the input data into subcarriers.

However as SNR is increased, AMCl will discard the low order schemes from

mapping process.

The boundaries of low SNRs are different in each tested mode. For example in

modes that includes 256-QAM, the expression (low SNRs) is usually referring to

SNRs those below 8 dB. Utilizing the high order modulation scheme together with

low order scheme will enhance the data throughput. The utilization percentage in

model (1) is controlled by appropriate definition of the clipping ratio (CR) of each

utilized modulation scheme.

AMCl employs updating mechanism to define the appropriate the CR of the

selected scheme based on the estimated value of SNR. In this mechanism, the value of

CR is classified into three categories in terms of clipping level namely high CR (soft

clipping), low CR (hard clipping), and moderate CR. Each category of clipping level

is assigned to group of SNRs.

96

Based on the boundaries of those SNRs the appropriate value of CR will be

selected. This means that the clipping intensity of OFDM samples at any SNR will be

different and depends on the utilized modulation scheme. To conclude the value of CR

in updating mechanism depends on the order of modulation scheme and SNR.

Figure 3.6 shows the selection policy of modulation schemes in the proposed

model (1). As the range is increased from the base station (low SNR value) the

decision of selection the proper modulation scheme will be made based on the value

of SER which can be calculated from the last successful symbol transmission.

For example at SNR= 12 dB, which is the threshold value of the low order

modulation scheme 4-QAM (refer to Table 2.5). The conventional selection policy in

AM will select 4-QAM to map the data, whereas in mode (A) of model (1), with the

proposed selection policy the decision will be made to use 256-QAM, 128-QAM, 64-

QAM, 16-QAM, or 4-QAM.

Each modulation scheme will be used to map a certain number of subcarriers

based on SER. The CR must be defined for each modulation scheme and adapted

based on the SNR in order to keep SER under an accepted value. This accepted value

depends on the selected mode in model (1).

Figure 3.6 The proposed modulation selection policy

128, 256- QAM

256-QAM 16, 64, 128, 256-

QAM

97

AMCl algorithm in model (1) is shown in Figure 3.7. Based on the value of

SER that is calculated from the last successful symbol transmission, the decision of

choosing the order of modulation scheme can be made. The SER has been defined

with a various real values as follows: SER= [0, r1, r2, r3, r4 ..., rn,

, 1] , Each value is

assigned to a certain modulation scheme as shown in Table 3.4.

Table 3.4 SER switching values of modulation selection policy in model (1)

SER Modulation scheme

0 ≤ SER < r 256-QAM 1

r1 ≤ SER < r 128-QAM 2

r2 ≤ SER < r 64-QAM 3

r3 ≤ SER < r 16-QAM 4

r4 4-QAM ≤ SER< 1

This value defines the number of error bits in one OFDM symbol. For example

if SER is greater than or equal to r1 and less than r2

, the decision will be made to

choose the high order modulation scheme 128-QAM to be used as a mapping

technique for the OFDM system in the current transmission. This means that the job

of SER is to recommend the best modulation scheme for the system.

AMCl can change the switching values of SER to meet the channel condition.

These changes will vary the utilization percentage in each mode. For example if the

received SER of OFDM signal is high with high modulation schemes such as

256QAM, and 128-QAM at low SNR of 5 dB, there are two reactions that AMCl can

do. The first one is switching to other modes that do not utilize these high schemes,

whereas second reaction is changing the SER thresholds of these high schemes to

small values and this will discards them from mapping process at SNR equal to or less

than 5 dB.

98

Figure 3.7 AMCl algorithm in model (1)

Yes

No

No No No No

Yes Yes Yes Yes

Receive the OFDM signal

SER calculation SER= [0, r1, r2, r3, r4..., rn, 1]

Define and update the CR based on the order of the modulation scheme and SNR

If y > + [A1, A2..., A5] or y < - [A1, A2.., A5]

Transmit the OFDM signal

Clip the OFDM signal

Modulation level

256-QAM 64-QAM 128-QAM 4-QAM 16-QAM

If r1≤SER<r2

If 0≤SER<r1

If r2≤SER<r3

If r3≤SER<r4

Choosing the modulation scheme based on SER value

SNR estimation

99

The problem here is how to avoid the toggle situation in each mode between

the highest modulation scheme such as 256-QAM and the lowest scheme such as 4-

QAM.

In order to prevent this situation, there must be a way to prevent clipping the

samples that are modulated using high order scheme at low CR, and prevent clipping

samples that are modulated using low order scheme at high CR. To solve this problem

AMCl employs updating mechanism of the CR of each modulation scheme.

3.10.2 CR Definition and Updating Mechanism in Model (1)

The utilization percentage of the modulation schemes is controlled by CR which in

turn depends on the channel condition. In addition the value of CR is defined based on

the order of the modulation scheme that is utilized in the current transmission.

Updating the value of CR at each new symbol transmission is important to ensure that

the OFDM samples will not clipped with wrong clipping level.

At low SNR, clipping the samples at low CR will reduce PAPR, whereas the

SER performance will be degraded seriously. However at high SNR, clipping these

samples at high CR will keep PAPR at high level and avoid serious degradation in

SER.

At all SNRs, there are appropriate CR can be chosen to make compromise

between PAPR improvement and an accepted SER performance and this is the

mission of CR updating mechanism. AMCl algorithm always tries to control the

percentages of utilizing the modulation schemes in all tested modes of model (1).

Appropriate definition of the clipping level in each modulation schemes is

essential to obtain a reasonable reduction in PAPR without causing serious

degradation in SER performance. Because of the high peaks in OFDM samples are

rarely happen. This will make the definition of CR for each modulation scheme is

tough mission.

100

The purpose of this mechanism is to keep the SER under an accepted value

which depends on the tested mode. Moreover this mechanism must ensure the

utilization of all available modulation schemes at low SNRs (less than 8 dB), and

discard the low order modulation schemes as the SNR is increased. The percentage of

using all the modulation schemes can be defined and controlled by a careful selection

of the clipping level A = [ A1, A2, A3, A4, A5

] for each modulation scheme, and this is

a quite difficult job. Actually it needs a long observation of the behaviour of the

OFDM signal over a long time of transmission. This is because of the changing nature

of OFDM signal and the high peaks samples are very rare to happen during the

transmission of the OFDM symbols.

In addition the fluctuation in the envelope of OFDM signal increases as the

order of the modulation scheme is increased. A long observation for the OFDM signal

in time domain at different SNRs can help to classify the CRs into three categories

which are high, moderate, and low. The updating mechanism assigns SNR boundaries

for each utilized modulation scheme. These boundaries of low modulation scheme

may be nested with other boundaries of another high order modulation scheme. This

means that the degree of clipping (soft or hard) may be different for two different

order of modulation scheme at the same SNR.

Table 3.5 lists the boundaries of CR for all M-QAM modulation schemes.

These boundaries will be used by AMCl to update the value of CR after each symbol

transmission to meet the channel condition instead of using constant CR at all SNRs.

As mentioned before, AMCl in model (1) employs updating mechanism to define and

update the values of CRs β1 and β2 based on SNR thresholds of each modulation

scheme.

Table 3.5 Clipping ratio definitions in AMCl of model (1)

Modulation scheme CR class CR thresholds SNR thresholds

M-QAM

High CR≤ β1 0≤SNR<γ1

Moderate β1<CR< β2 γ1≤SNR<γ2

Low CR≥ β2 γ2≤SNR

101

For example in mode (A), when utilizing 64-QAM as mapping scheme the

decision will be made to clip OFDM signal with high CR at SNR smaller than 12 dB,

whereas the low CR can be used at SNR equal or greater than 16 dB as listed in Table

3.6.

Table 3.6 Clipping ratio definitions in the tested mode (A)

Modulation scheme CR value CR thresholds SNR thresholds 4-QAM High CR≥0.8 0≤SNR<5

Moderate 0.2<CR<0.8 5≤SNR<8

Low CR≤ 0.2 8≤SNR

16-QAM High CR≥1.4 0≤SNR<8

Moderate 0.6<CR<1.4 8≤SNR<10

Low CR≤ 0.6 10≤SNR

64-QAM High CR≥1.8 0≤SNR<12

Moderate 0.8<CR<1.8 12≤SNR<16

Low CR≤ 0.8 16≤SNR

128-QAM High CR≥2.0 0≤SNR<14

Moderate 1.4<CR<2.0 14≤SNR<18

Low CR≤ 1.4 18≤SNR

256-QAM High CR≥2.5 0≤SNR<18

Moderate 1.8<CR<2.5 18≤SNR<22

Low CR≤ 1.8 22≤SNR

The proposed AMCl algorithm in model (1) will try to enhance the data

throughput of OFDM system at all SNRs and offer better improvement in PAPR.

Moreover it will try to make the value of SER of the tested modes better than the

normal OFDM system with high schemes such as 64-QAM, 128-QAM and 256-

QAM. This improvement in SER depends on the tested mode. In the next chapter, all

these aspects will be discussed in details.

102

3.10.3 The Algorithm AMCl in Model (2)

The modulation selection policy in model (2) is controlled by SNR and SER. In other

words the values of SNR and SER will be used together to decide which modulation

schemes must be selected. In this model one or two modulation schemes as maximum

could be selected at each SNR. In other words, two modulation schemes can be

candidate to be the mapping scheme at the same SNR, but the final decision of

selection will be made based on SER.

The utilization percentage of modulation scheme in model (2) is also

controlled by CR as in model (1). The difference in model (2) is absent of CR

updating mechanism. The OFDM signal will be clipped at constant CR at all SNRs.

Two values of CR (high and low) are assigned to each modulation scheme. The CR

thresholds or boundaries are defined based on long observation of the highest peaks of

OFDM signal with each utilized modulation schemes. These thresholds of CR in

model (2) are defined based on the target value of SER.

Figure 3.8 shows only one stage of the algorithm AMCl that will be employed

in the tested modes D and E. This stage will be repeated many times depending on the

number of the modulation schemes that are utilized to map the OFDM symbols in

each mode. As mentioned before the conventional selection policy of AM utilize only

one modulation scheme at each SNR. If SNR is low, low order modulation scheme

will be used as a mapping technique, therefore the system throughput will be low.

Moreover each modulation scheme is assigned to group of SNRs that called

thresholds. Within these thresholds the modulation scheme can offer reasonable and

stable SER performance. Even some OFDM symbols could be received with small

SER, the transmitter still receives the same SNR or SNR belong to low order

modulation scheme. This leads to constant throughput during each group of SNRs of

each modulation scheme.

103

AMCl algorithm in model (2) will use the SNR values to define which one of

the modulation schemes should be used to map the input data onto the carriers. Two

modulation schemes can be used to map the input data at each SNR. The values of

SNR in AMCl are classified to numbers of group. The number of groups depends on

the number of utilized modulation schemes in each tested mode.

For example in mode D that utilizes five modulation schemes, the number of

SNR group will be five. Therefore AMCl algorithm in mode D is consisted of five

stages. At each stage, one or two modulation schemes are utilized in mapping process.

In each stage there are three reference values of SNR and two values of SER. AMCl

will classify any estimated SNR and select the appropriate stage.

Based on both SNR and SER reference values in the selected stage, AMCl will

select the appropriate modulation scheme that can offer the target SER. AMCl will try

to give the priority of usage to the high order modulation schemes as the SNR value is

increases.

For example between the two values of SNR (4 dB and 8 dB), and based on

the value of SER the algorithm will give the priority to 4-QAM to be utilized as

mapping scheme at SNR of 4 dB, but as the value of SNR is increased toward 8 dB

the priority will be given to 16-QAM.

In Figure 3.8, two modulation schemes M1 and M2 are used to map the input

data. The order of modulation scheme M1 is greater than the order of modulation

scheme M2

. SNR has three values [v1, v2, v3] in dB. The SER has only two real

values, this because of this stage is only describing the proposed mechanism of

selection policy of adaptive modulation of two modulation schemes. As explained

before, when the value of SNR is increased from v1 toward v2, and based on the value

of the calculated SER from the last successful transmission, the modulation scheme

will be chosen. The clipping level will be defined based on the order of modulation

schemes and the target value of SER.

104

Figure 3.8 AMCl algorithm in model (2)

SER calculation

No

No

If SNR ≥ v3

and SER ≥ r1

M1- QAM

Yes

M2- QAM

Define CR based on the order of the modulation scheme and target SER

Clipping

No M2- QAM

If

v1≤SNR<v2 and

r1≤SER<r2

Yes

No

If

v1≤SNR<v3 and

SER ≥ r2

Yes

Yes

If v2≤SNR<v3

and r1≤SER<r2

M1- QAM

105

3.10.4 CR Definition and Updating Mechanism in Model (2)

As mention before the clipping ratio has an important function to monitor the

percentage of utilizing the modulation schemes and then keep the value of SER under

the target value. AMCl in the tested modes (D) and (E) will not employ any

mechanism for updating the CR of each modulation scheme at each new symbol

transmission. AMCl will define two values (high and low) of CR for each modulation

schemes. The values of CR have been classified based on the SER target value. These

values can be defined by long observation of the behaviour of OFDM samples in each

symbol. The difficulty in this observation is increased as the order of scheme is

increased due to the fluctuation in the OFDM symbol envelope becomes high.

The advantage of a constant definition of CR for each scheme is reducing the

complexity of AMCl and saving in the processing time. One important thing that can

help to define a constant value of CR is the nature of happening of high peaks in

OFDM samples. It is found that the high peaks are rare and can be measured using

this implemented simulation. Table 3.7 lists the definition of the clipping ratio for

each modulation schemes utilized in the tested modes of model (2). Each modulation

scheme has two constant values of CR (high or low). All tested modes in model (2)

will be validated in each OFDM system at high and low CRs in order to offer two

options in model (2) of OFDM systems.

The first one which uses low CR is OFDM system has better PAPR

improvement, less SER performance (under 10-3), and less throughput enhancement.

The second option which uses high CR can offer OFDM system has less PAPR

improvement, better SER performance (under 10-5

), and better throughput

enhancement. This means that the option with low CR is suitable for OFDM system

that suffers from high PAPR due to utilizing a large number of subcarriers such as

IEEE 802.16e. However the option with high CR is suitable for OFDM system that

utilizes small number of subcarrier and needs high data rate such as IEEE 802.11g and

4G systems.

106

Table 3.7 Clipping ratio definitions in AMCl of model (2)

Tar

get

SER

CR

Modulation Schemes

256-QAM 128-QAM 64-QAM 16-QAM 4-QAM

10 Low -3 3.4≤CR≤3.8 3.0≤CR≤3.2 2.6≤CR≤2.9 1.8≤CR≤2.2 1.1≤CR≤1.5

10 High -5 CR≥4.2 CR≥3.5 CR≥3.3 CR≥2.6 CR≥1.9

3.10.5 Data Rate Calculation in the Proposed Models (1) and (2)

In the proposed modulation selection in model 1, the symbols in one OFDM frame at

low SNRs will be modulated using all modulation schemes, whereas in model (2),

only two modulation schemes can be selected at each constant SNR value. The data

rate of the OFDM system can be calculated using the following equation:

s

subbs T

NNR ×= (3.22)

where Rs is the system data rate, Nb is the of bit per subcarriers, Nsub is the number of

data subcarriers, and Ts

is the useful symbol duration.

The number of bits that are carried in data subcarrier can be defined from the

number of constellation points in the modulation schemes. For example when OFDM

utilizes scheme 4-QAM there are 2 bits per subcarrier, whereas there are 8 bits per

subcarrier with 256-QAM. The data rate in the tested modes of the selection policy

models can be calculated as follows:

s

M

pm RUR ×= ∑1

(3.23)

where Rm is the data rate of tested mode, M is the total number of utilized modulation

schemes in the tested mode, Up is the utilization percentage of modulation scheme,

and Rs is the system data rate. The required time to transfer data from transmitter to

receiver in any tested mode can be calculated as follows:

107

m

s RDT = (3.24)

where Ts

is the transmission time and D is the data size

3.10.6 The Complexity in AMCl Algorithm

A suitable modulation level in adaptive modulation is selected according to the user's

channel quality. The utilization of AM in downlink (DL) requires the channel

information of each user on DL to properly select the modulation level. The proposed

algorithm AMCl in model (1) and (2) utilizes different orders of modulation schemes

to modulate the data onto subcarriers in each transmitted OFDM symbol. This leads to

necessity of informing the receiver about the modulation level of each subcarrier.

However, under a practical OFDM system environment, it is unsuitable to feedback

all the side information over the whole frequency resources due to the limited uplink

bandwidth.

In this thesis, to optimize the performance of the AM in OFDM system and to

reduce the uplink feedback requirement, a simple flexible block-wise loading

algorithm is employed in the proposed algorithm AMCl in both selection policy

models. AMCl allocates groups of subcarriers that utilize the same order of

modulation scheme to each user in DL based on the channel quality information. As a

result of group the subcarriers together to form subchannel, AMCl can reduce the

complexity due to the overhead in the transmitted data.

3.12 SUMMARY

Two models of modulation selection policy in AM are presented in this chapter. The

combination of these models with the clipping techniques introduces an algorithm

called adaptive modulation and clipping (AMCl). The proposed algorithm is

employed in all tested modes of each models.

108

Each mode utilizes a number of modulation schemes. The algorithm AMCl in

each mode controls the utilization percentage of all modulation schemes. This

algorithm will be validated in three known OFDM based wireless systems namely

IEEE 802.11g, IEEE 802.16e, and 4G.

In model (1) the selection policy is based on the calculated SER from last

successful symbol transmission. In addition AMCl employs updating mechanism that

can define and update the value of CR at each transmission based on the order of

modulation scheme and the estimated SNR. However in model (2) the modulation

selection policy is based on the values of both SER and SNR. AMCl defines the value

of CR based on order of modulation scheme and the target value of SER.

In both models the definition of CR is an important issue and represents a

restriction to any compromoise between SER and PAPR. It is essential to propose a

method that can offer possibility to get the advantage of clipping technique by

clipping OFDM signal at low CR without to produce better improvement in PAPR

and avoid any serious degradation in SER performance due to in-band distotion.

CHAPTER IV

ADAPTIVE MODULATION SELECTION POLICY MODELS

4.1 INTRODUCTION

The importance of OFDM stands behind the purpose of this thesis. Two models of

modulation selection policy in AM are proposed. Each model includes numerous of

tested modes that employ different orders of modulation schemes as was explained in

chapter 3. These models are combined with the simplest PAPR reduction technique

which is the clipping technique to produce an algorithm called AMCl. The modulation

schemes in model (1) are selected based on SER which in turn depends on the value of

clipping Ratio (CR). The definition of SNR thresholds for each modulation scheme is

different in each mode.

The proposed AMCl algorithm in model (1) utilizes all available modulation

schemes in each mode especially at low SNRs. However AMCl discards the low order

schemes from mapping process as the SNR is increased. The CR in model (1) is

classified into three categories in terms of clipping intensity namely high, moderate,

and low. The definition of CR depends on the order of modulation scheme and SNR.

The boundaries or thresholds of CR are defined based on the SNR thresholds of each

modulation scheme. AMCl algorithm at each new symbol transmission employs CR

updating mechanism to define the appropriate value of CR of each modulation scheme

at all SNRs. The CR updating mechanism defines the utilization percentage of the

modulation schemes at each SNR.

110

In addition this updating mechanism can keep the SER under an accepted

value that depends on the tested mode. This can be done by careful selection of CR at

each symbol transmission and monitor the estimated SNR to update the value of CR

for each modulation scheme. The OFDM signal at low SNRs is clipped using high CR

(soft clipping), whereas at high SNRs it will be clipped using low CR (hard clipping).

The moderate CR can be used at some SNRs when it can make compromise

between PAPR improvement and SER degradation. Because of the thresholds of SNR

are different for each modulation scheme, the OFDM signal in each subcarrier is

clipped at different CRs. In addition, AMCl algorithm detects the improvement in

SER and switch CR from low, moderate and to high value.

The selection policy in model (2) chooses the modulation scheme based on

SNR. The utilization percentage of each modulation scheme is SER controlled. AMCl

algorithm in model (2) utilizes one or two modulation schemes as maximum at each

SNR. The modulation schemes with adjacent order will be utilized together such as

(4-QAM and 16-QAM) or (16-QAM and 64-QAM) and so on.

Unlike model (1), the CR in model (2) is constant for each modulation scheme

at all SNRs. Two values of CR are defined in the tested modes of model (2) namely

low CR (hard clipping) and high CR (soft clipping). The definition of CR in model (2)

is based on the target SER. By long observation of many OFDM symbols the decision

of appropriate clipping level that can keep the SER under the target value can be

made. The most important challenge in the proposed AMCl is the definition of CR in

order to achieve improvement in PAPR and reasonable SER performance.

111

4.2 PERFORMANCE OF NORMAL OFDM SYSTEM

4.2.1 Order of Modulation Scheme

The word (normal) refers to OFDM system that does not employ neither AM nor

clipping technique. Figure 4.1 shows the SER performance of normal OFDM for

different modulation schemes. It can be seen from this figure that the lower

modulation scheme provides better performance with less SNR. This can be easily

visualized by a simple look at their constellation mapping; larger distance between

adjacent points can tolerate larger noise. The small frequency separation between two

sub-carriers makes them more vulnerable to the ICI due to the frequency offset

introduced by the Doppler spread of the channel.

0 5 10 15 20 25

10-6

10-5

10-4

10-3

10-2

10-1

100

SNR (dB)

SER

Normal OFDM-BPSKNormal OFDM-4QAMNormal OFDM-16QAMNormal OFDM-64QAMNormal OFDM-128QAMNormal OFDM-256QAM

Figure 4.1 SER performance of normal OFDM-IEEE 802.16e system with different order of modulation schemes

112

In order to achieve SER performance below 10-5

in Figure 4.1, the SNR

thresholds of each modulation scheme should follow the boundaries that are listed in

Table 4.1. These thresholds will be used as a reference in the performance comparison

between proposed modes and normal OFDM system.

Table 4.1 AWGN switching thresholds for conventional selection policy

Modulation scheme SNR threshold (dB)

BPSK 0<SNR≤8

4QAM 8<SNR≤14

16QAM 14<SNR≤18

64QAM 18<SNR≤20

128QAM 20<SNR≤24

256QAM 24<SNR

Figure 4.2 shows the scatter plots for different modulation schemes as SNR

values are changed. The (+) symbol denotes the transmitted data and the (*) symbol

denotes the received data. It can be observed from these plots that spread reduction is

taking place with the increasing values of SNR.

113

This scenario validates the implementation of channel model. It is also very

important to note that the scatter spread gives a strong hint about the BER/SER

statistics as SNR values are varied.

-4 -3 -2 -1 0 1 2 3 4-4

-3

-2

-1

0

1

2

3

4 4-QAM (SNR=8 dB)

Real axis

Imag

inar

y ax

is

Recieved dataTransmitted data

(a)

-6 -4 -2 0 2 4 6

-6

-4

-2

0

2

4

6

16-QAM (SNR=16 dB)

Real axis

Imag

inar

y ax

is

Received dataTransmitted data

(b)

114

-10 -5 0 5 10

-10

-5

0

5

10

64-QAM (SNR=25 dB)

Real axis

Imag

inar

y ax

is

Received dataTransmitted data

(c)

-20 -15 -10 -5 0 5 10 15 20

-20

-15

-10

-5

0

5

10

15

20

256-QAM (SNR=30 dB)

Real axis

Imag

inar

y ax

is

Received dataTransmitted data

(d)

Figure 4.2 Scatter plots of normal OFDM-IEEE802.16e with different order of modulation schemes (a) 4-QAM, (b) 16-QAM, (c) 64-QAM, (d) 256-QAM

115

4.2.2 Cyclic prefix and number of subcarriers

ICI occurs when the multipath channel varies over one OFDM symbol time (Bahai

and Burton 1999). When this happens, the Doppler shift on each multipath component

causes a frequency offset on the sub-carriers, resulting in the loss of orthogonality

among them. ICI also occurs when an OFDM symbol experiences ISI. This situation

can be viewed from the time domain perspective, in which the integer number of

cycles for each sub-carrier within the FFT interval of the current symbol is no longer

maintained due to the phase transition introduced by the previous symbol.

Finally, any offset between the sub-carrier frequencies of the transmitter and

receiver also introduces ICI to an OFDM symbol. If the guard period is left empty, the

orthogonality of the sub-carriers no longer holds. In order to eliminate both the ISI as

well as the ICI, the OFDM symbol is cyclically extended into the guard period. This

preserves the orthogonality of the sub-carriers by ensuring that the delayed versions of

the OFDM symbol always have an integer number of samples within the FFT interval.

OFDM is resilient to ISI because its symbol duration is long compared with

the data symbols in the serial data stream. For an OFDM transmitter with N sub-

carriers, if the duration of a data symbol is T’, the symbol duration of the OFDM

symbol at the output of the transmitter is:

Ts

=T’ N (4.1)

where T’ is duration of a data symbol and N is total number of sub-carriers. Thus if the

delay spread of a multipath channel is greater than T’ but less then Ts

, the data symbol

in the serial data stream will experience frequency-selective fading while the data

symbol on each sub-carrier will experience only flat-fading.

Figures 4.3, 4.4, and 4.5 show the effect of CP length on scatter plot with

constant SNR value of different modulation schemes in IEEE 80216e system. The

differences are clearly visible that the scatter plots are less scattered for higher values

of CP length. Because, the capabilities to absorb multipath effects increases with

higher value of CP length.

116

-4 -3 -2 -1 0 1 2 3 4-4

-3

-2

-1

0

1

2

3

4 (G=1/32) (SNR=4 dB)

Real axis

Imag

inar

y ax

is

(a)

-4 -3 -2 -1 0 1 2 3 4-4

-3

-2

-1

0

1

2

3

4 (G=1/16) (SNR=4 dB)

Real axis

Imag

inar

y ax

is

(b)

117

-4 -3 -2 -1 0 1 2 3 4-4

-3

-2

-1

0

1

2

3

4 (G=1/8) (SNR=4 dB)

Real axis

Imag

inar

y ax

is

(c)

-4 -3 -2 -1 0 1 2 3 4-4

-3

-2

-1

0

1

2

3

4 (G=1/4) (SNR=4 dB)

Real axis

Imag

inar

y ax

is

(d)

Figure 4.3 Scatter plots of normal OFDM-4QAM-IEEE 802.16e system with

different CP length (a) CP=1/32, (b) 1/16, (c) 1/8, (d) 1/4

118

(a)

(b)

119

(c)

(d)

Figure 4.4 Scatter plots of normal OFDM-64QAM-IEEE 802.16e system with

different CP length (a) CP=1/32, (b) 1/16, (c) 1/8, (d) 1/4

120

(a)

(b)

(c)

Figure 4.5 Scatter plots of normal OFDM-256QAM-IEEE 802.16e system

with different CP length (a) CP=1/32, (b) 1/8, (c) 1/4

121

After reviewing all above figures, the effect of the number of sub-carriers and

guard time duration on the system performance can be summarized as follows:

a. For a given number of sub-carriers, increasing guard time duration reduces ISI

due to the decrease in delay spread relative to the symbol time, but reduces the

power efficiency and bandwidth efficiency.

b. For a given signal bandwidth, increasing the number of sub-carriers increases

the power efficiency but also increases the symbol duration and results in a

system more sensitive to Doppler spread.

Figure 4.6 shows the 16QAM signal constellation diagrams for four OFDM

systems with 128, 256, 512, and 1024 sub-carriers respectively. The effect of

increasing the number of subcarriers can be noticed on the extending the duration of

the OFDM symbol, and this leads to degradation in SER performance due to ISI.

The points in Figure 4.6 become less scattered as the number of subcarriers is

decreased. In addition, it is clear to note that the less order modulation scheme the

better improvement in SER can be achieved. This is because of increasing the bit

loading in each transmitted OFDM symbol as the order of modulation scheme is

increased. In other words the effect of applying cyclic prefix on OFDM system

becomes less as the number of bits per symbol is increased.

The two-ray channel is time-varying with each path having Doppler frequency

of 120Hz. From the Figure, it shows that the signal constellation diagram for the

1024-sub-carriers OFDM system is more blurred than the 256 sub-carrier and 512-

sub-carrier OFDM systems. For a given signal bandwidth, the frequency spacing

between sub-carriers decreases as the number of sub-carrier increases.

122

-6 -4 -2 0 2 4 6

-6

-4

-2

0

2

4

6

Received signal Constellation (1024 subcarriers)

Real axis

Imag

inar

y ax

is

(a)

-6 -4 -2 0 2 4 6

-6

-4

-2

0

2

4

6

Received signal Constellation (512 subcarriers)

Real axis

Imag

inar

y ax

is

(b)

123

-6 -4 -2 0 2 4 6

-6

-4

-2

0

2

4

6

Received signal Constellation (256 subcarriers)

Real axis

Imag

inar

y ax

is

(c)

-6 -4 -2 0 2 4 6

-6

-4

-2

0

2

4

6

Received signal Constellation (128 subcarriers)

Real axis

Imag

inar

y ax

is

(d)

Figure 4.6 Scatter plots of normal OFDM-16-QAM-IEEE 802.16e system with

different number of sub-carriers at SNR of 10 dB (a) Nsub 512, (c) 256, and (d) 128

=1024, (b)

124

4.2.3 Processing and multipath delay

There is delay produced in the OFDM system was generated from the reconstruction

filtering process. Figure 4.7 (a), and (b) shows the effect of the reconstruction filter

process on the OFDM-IEEE802.16e received signal.

The reconstruction filter produced the delay that was enough to impede the

reception and caused the slight difference between the transmitted signal and the

received signal.

The maximum correlation is achieved at a delay of 63

T

. Thus, the delay

produced by the reconstruction and demodulation filters is about:

d SP63 = = 7.0314×10-9

sec

(4.2)

where SP is the simulation period that can be calculated as follows:

SP = 4× f

c

ICI reduction is only meaningful when Doppler shift is large and SNR is high.

The next two examples of users with different speed will try to calculate the value of

normalized Doppler shift, and find out if the reduction of ICI is really meaningful for

this Mobile WiMAX OFDM system or not. fd

is the maximum Doppler shift

cfv

f cd

.= (4.3)

The carrier frequency fc = 2.3 GHz, the Useful symbol duration Ts

= 91.43 µs,

the bandwidth of one channel B = 10 MHz, the total number of subcarriers N = 1024,

and the duration of cyclic prefix CP = 1/8. The user with low mobility (pedestrian

with speed 3 km/h)

8

9

103103.2833.0

×××

=df

Hz39.6=

125

The subcarrier bandwidth (Carrier spacing)

U

k TNBB 1== where 0 ≤ k ≤ N-1 (4.4)

= 10.94 KHz The normalized Doppler shift

k

d

Bf

94.1039.6 =

= 0.58

The user with high mobility (vehicle travelling 200 km/h)

cfv

f cd

.=

8

9

103103.256.55

×××

=

= Hz96.425

The normalized Doppler shift

k

d

Bf

94.1096.425

=

94.38=

As the normalized Doppler shift is really high, and with a good SNR

condition. So the reduction of ICI is really meaningful for this system.

126

7.6 7.65 7.7 7.75 7.8 7.85

x 10-7

37

37.5

38

38.5

39

39.5

40

40.5

Time response of the OFDMA transmitted signal & received signal (Inphase)

Time (sec)

Ampl

itude

(v)

OFDMA-4QAM transmitted signalOFDMA-4QAM received signal

(a)

1.56 1.58 1.6 1.62 1.64 1.66 1.68 1.7 1.72 1.74 1.76

x 10-7

350

360

370

380

390

400

410

420

Time response of the OFDMA transmitted signal & received signal (Inphase)

Time (sec)

Ampl

itude

(v)

OFDMA-256QAM transmitted signalOFDMA-256QAM received signal

(b)

Figure 4.7 Time response of the transmitted and received signals of normal IEEE 802.16e system with (a) 4-QAM, and (b) 256-QAM

127

Figure 4.8 shows the cross-correlation of the transmitted and received OFDM-

IEEE802.16e signal.

0 50 100 150 200 250 300 350 400 450 500

-2

0

2

4

6

8

10

12

14

16

x 109

corre

latio

n w

ithou

tnor

mal

izat

ion

lag

Figure 4.8 Correlation of transmitted and received OFDM-IEEE80216e signals

Figure 4.9 (a), and (b) shows the effect of multipath environment on this

system. It is easy to note the delay in receiving the OFDM signal on path 2. This delay

is about (1.4063×10-7

sec) which equals 20 times the delay caused by reconstruction

filter.

The difference in transmission time between paths 1 and 2 is less than the

length of the defined guard time (Tg) in OFDM- IEEE802.16e that equals to

(1.143×10-5 sec). Moreover the total delay (that is about 1.477×10-7 sec) in OFDM-

IEEE802.16e system caused by the reconstruction filter, demodulation process, and

multipath is also less than the defined guard time. In this case ICI and ISI will not

occur.

128

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

x 10-6

-80

-60

-40

-20

0

20

40

60

Time (sec)

Ampl

itude

(v)

OFDMA-4QAM signal on path 1OFDMA-4QAM signal on path 2

(a)

2 3 4 5 6 7 8

x 10-7

-500

-400

-300

-200

-100

0

100

200

300

400

Time (sec)

Ampl

itude

(v)

OFDMA-256QAM signal on path 1OFDMA-256QAM signal on path 2

(b) Figure 4.9 Effect of multipath on the IEEE 802.16e of OFDM received baseband signal with (a) 4-QAM, and (b) 256-QAM

129

Figure 4.10 shows the effect of using the zero padding to reduce the effect of

ICI and IBI on the OFDM-16QAM system due to insertion zeros at the end of each

symbols block. Because of ZP does not suffer from zero channel location as CP, the

transmitted symbols can be recovered. It is easy to note the improvement in the scatter

plots after applying the Zero padding (ZP). It is easy to conclude that the improvement

in SER after using zero padding is better in the lower order modulation schemes than

higher order schemes. When OFDM system utilizes high order modulation schemes,

the duration of the transmitted symbol is extended due to increasing the bit loading per

symbol. Despite using zero padding, the extension in symbol duration makes the

system more susceptible to the ISI and ICI and causing degradation in the SER.

-6 -4 -2 0 2 4 6

-6

-4

-2

0

2

4

6

without Zero Padding, (SNR=12)

Real axis

Imag

inary

axis

(a)

-6 -4 -2 0 2 4 6

-6

-4

-2

0

2

4

6

with Zero Padding, (SNR=12)

Real axis

Imag

inary

axis

(b)

Figure 4.10 Scatter plots of normal OFDM-IEEE 802.16e-16QAM system

(a) without, and (b) with Zero Padding

130

4.3 EFFECTS OF CLIPPING RATIO

This thesis introduces models of modulation selection policy in adaptive modulation

that are combined together with the clipping technique to produce a new algorithm

which is called Adaptive Modulation and Clipping (AMCl) algorithm. This algorithm

should achieve two goals, the first one is to reduce the PAPR, and the second one is to

enhance the data rate especially at low SNR values without degrade the SER

performance.

4.3.1 CR and the modulation schemes order

The peak problem in OFDM becomes worse when utilizing higher order modulation

schemes. This is because of the nature of the envelope of OFDM signal that suffers

from high fluctuations between the high and low peaks. Defining appropriate clipping

level in OFDM signal depends on the order of modulation schemes. The difficulty in

the mission of defining the CR increases as the number of transmitted bits in each

subcarrier increases. Long observation of the envelope of one OFDM symbol provides

good information about the value of high peaks and makes the calculation of CR

easier.

In order to simply the mission of the CR definition mechanism, it is essential

to define formula that can help to find out the appropriate value of CR. The simplest

way to define this appropriate value is to calculate the CR of the lower order

modulation schemes which is 4-QAM because of having low fluctuation in its

envelope. Recall Equation 2.23 and 3.9, the value of high CR of M-QAM schemes can

be calculated as follows:

102CR High

QAM4QAM-M

kA+

=

−σ (4.5)

where k = log

2

M , A is the clipping level, and σ is the root mean squared (RMS)

power of the unclipped OFDM signal.

131

However, the low value of CR in M-QAM modulation scheme can be

calculated as follows:

(4.6) 10

CR Low QAM4

QAM-MkA

+

=

−σ

The effect of increasing the order of modulation scheme on the definition of

the value of CR can be noticed in Figure 4.11. As the number of transmitted bits in

each level of the modulation scheme increases the amplitude of OFDM peaks

increases and then the value of clipping level should be increased in order to reduce

the amount of the clipped samples in OFDM signal.

5 10 15 20

0.5

1

1.5

2

2.5

3

3.5

SNR (dB)

CR

4-QAM 16-QAM 64-QAM128-QAM256-QAM

k=2

k=4 k=6

k=7 k=8

Figure 4.11 Clipping ratio as function of the modulation schemes order

However, AMCl in both proposed models employs mechanism to define and

update the value of CR based on the order of the utilized modulation schemes. Other

performance metrics play key role in defining the appropriate value of CR in each

OFDM symbol transmission such as the target SER and SNR. The CR definition

mechanism takes into account all this metrics in updating the value of clipping level.

132

For example when defining the values of CR based on SNR, the clipping level

always changes to meet the channel conditions. In other words when the estimated

SNR is low the mechanism defines high CR to decrease the amount of clipped peaks

and then maintain the error level under the accepted value. As the value of SNR

increases the CR is decreased to low values. This means that the CRs for various

modulation schemes that are utilizes to modulate subcarriers in one OFDM symbol are

different as shown in Figure 4.12.

5 10 15 200

0.5

1

1.5

2

2.5

3

3.5

4

SNR (dB)

CR

4-QAM 16-QAM 64-QAM128-QAM256-QAM

k=8

k=7

k=6

k=4

k=2

Figure 4.12 CR definition mechanism in the proposed modulation selection models

4.3.2 Clipping ratio and percentage of the clipped samples

When using the clipping scheme, the phase information of the signal is completely

transmitted, and the amplitude of the signal is clipped if the power of the signal

exceeds the maximum permitted power.

133

If using ideal power control to counteract the influence of wireless channel in

systems and not considering other factors (such as frequency set-off), the received

signal amplitude also shows as the same as the original signal plus to AWGN.

Although PAPR is very large for OFDM especially for large number of subcarriers as

in terrestrial digital video broadcasting (DVB-T) system, high magnitude peaks occur

relatively rarely and most of the transmitted power is concentrated in signals of low

amplitude.

Table 4.2 shows the percentage of the clipped samples of the original OFDM

signal at different CRs for various modulation schemes. It easy to note that the higher

the clipping ratio, the less number of OFDM samples will be clipped. According to

Equation 3.28, the percentages of clipped peaks in one OFDM symbol can be

calculated as follows

100(%) ×=p

clpper N

NC

For example in DVB-T system at SNR=18 dB, and clipping OFDM-256QAM

at moderate CR of 2.3. The total number of samples or peaks in one OFDM symbol is

102401. It is found that the number of clipped peaks is 12305. Recall Equation 3.28;

the clipping percentage is equal to

10010240112305(%) ×=perC

= 12.02

The high order modulation scheme such as 256-QAM needs higher CR than

low order schemes to offer the same clipping percentage because of the peak problem

becomes more serious when using higher order modulation schemes. In other words,

the fluctuation in OFDM-256QAM between the high and low peaks becomes larger

than in OFDM-16QAM. This means that the values of CR in OFDM-256QAM will be

higher than other modulation schemes to avoid wasting in the system bandwidth due

to sending large amount of clipped peaks to the receiver.

134

Table 4.2 Percentages of clipped OFDM-DVB-T samples at different CRs

CR class Clipping Ratio (CR) Modulation scheme Percentage of

clipping % Low 1.6 256-QAM 16.41

0.9 64-QAM 16.37

0.6 16-QAM 15.28

Moderate 2.8 256-QAM 7.16

1.6 64-QAM 6.94

1.1 16-QAM 5.78

High 3.5 256-QAM 0.99

2.1 64-QAM 0.86

1.5 16-QAM 0.80

Table 4.3 lists the thresholds value of CR for each modulation scheme. Values

of CR are classified into three categories namely high, moderate, and low for each

modulation scheme. This classification is based on calculation the percentage of

clipped peaks in one OFDM symbol as mentioned before. It is important to define the

CR carefully to get a good reduction in the PAPR without degrade the SER

performance as will be discussed later in the next sections. Three values of CR are

defined in the clipping technique that will be employed in the proposed AMCl

algorithm. These values are classified into three categories, high, moderate, and low.

The clipping process is called hard when using low CR, whereas it is soft clipping

when using high CR. The OFDM samples are clipped at high, moderate, and low

clipping ratio to investigate the effect of the clipping technique on the SER

performance of the OFDM system.

135

Table 4.3 Classification of CRs based on the percentage of clipped samples in OFDM-DVB-T system

Modulation scheme CR class CR thresholds 4-QAM Low CR≤ 0.6

Moderate 0.6<CR<1.2

High CR≥1.2

16-QAM Low CR≤ 0.8

Moderate 0.8<CR<1.6

High CR≥1.6

64-QAM Low CR≤ 1.2

Moderate 1.2<CR<2

High CR≥2

128-QAM Low CR≤ 1.8

Moderate 1.8<CR<2.5

High CR≥2.5

256-QAM Low CR≤ 2.2

Moderate 2.2<CR<3

High CR≥3

4.3.3 Clipping ratio and SER performance

The low CR can reduce the PAPR but caused degradation in the performance of the

SER. Figure 4.13 shows PAPR as a function of the clipping ratio. The PAPR of the

unclipped OFDM-IEEE802.16e signal is 15.6 dB. This means that for large CR the

OFDM signal x(t) is unclipped, but as CR converges to 0, the peak and average power

converge to 0 dB. For CR between 0.5 to 2 dB, the OFDM signal x(t) is clipped. In

this region it is easy to note the effectiveness of the clipping technique. It is essential

to choose the appropriate clipping level for each modulation scheme to get better

reduction in the PAPR and avoid any degradation in the performance of the SER.

136

0.5 1 1.5 2 2.5 3

2

4

6

8

10

12

14

16

Peak

-to-a

vera

ge p

ower

ratio

(dB)

clipping ratio (dB)

Figure 4.13 PAPR of Normal OFDM-IEEE 802.16e signal with 256QAM as a function of CR

It was shown the subcarriers that are modulated using low order modulation

scheme such 4-QAM can be clipped hardly and in the same time maintain the SER

value under the accepted value. As mentioned before, clipping causes in-band noise,

which causes degradation in the SER performance. Figure 4.14 shows the SER

performance as a function of the received signal-to-noise ratio (SNR), averaged across

all the subchannels, with different clipping ratios over a channel of additive white

Gaussian noise. In OFDM with 16-QAM, for low CR of 0.4 which represents hard

clipping, the degradation is more than 11 dB at the 10-2 SER level. However when CR

is about 0.7, less than a 7 dB penalty is encountered. At 10-4 SER level the

degradation is about 8 dB with moderate CR of 0.7. In OFDM with 64-QAM, for high

CR of 2.3, the SER degradation is only 0.8 dB at the 10-2 SER level, whereas at 10-4

SER level, less than a 0.7 dB penalty is encountered. To conclude for all modulation

schemes, high CR can be used at low SNRs without causing any degradation in SER,

but the reduction in PAPR will be small. Using low CR will improve PAPR, but it

must be used only at high SNRs to keep SER under an accepted value. However at

high SNRs it is possible to reduce PAPR without degrade SER by using moderate CR.

Because this values of CR at high SNRs offers SER better than low SNRs.

137

2 3 4 5 6 7 8 9 10

10-6

10-5

10-4

10-3

10-2

10-1

4-QAM

SNR (dB)

SER

Normal OFDM-4QAMClipped OFDM-4QAM (CR=0.9)Clipped OFDM-4QAM (CR=0.4)Clipped OFDM-4QAM (CR=0.2)

(a)

5 10 15 20 25

10-6

10-5

10-4

10-3

10-2

10-1

SNR (dB)

SER

16-QAM

Normal OFDM-16QAMClipped OFDM-16QAM (CR=1.8)Clipped OFDM-16QAM (CR=0.7)Clipped OFDM-16QAM (CR=0.4)

(b)

138

5 10 15 20 25 30

10-6

10-5

10-4

10-3

10-2

10-1

100 64-QAM

SNR (dB)

SER

Normal OFDM-64QAMClipped OFDM-64QAM (CR=2.3)Clipped OFDM-64QAM (CR=1.2)Clipped OFDM-64QAM (CR=0.7)

(c)

5 10 15 20 25 30

10-6

10-5

10-4

10-3

10-2

10-1

100 256-QAM

SNR (dB)

SER

Normal OFDM-256QAMClipped OFDM-256QAM (CR=3.1)Clipped OFDM-256QAM (CR=1.9)Clipped OFDM-256QAM (CR=1.3)

(d)

Figure 4.14 SER of the clipped OFDM-IEEE 802.16e signal for different CRs with (a) 4-QAM (b)16-QAM (c) 64-QAM and (d) 256-QAM

139

Table 4.2 shows the degradation in the SER performance after clipping the

OFDM samples hardly using different CRs for different order of modulation schemes.

The advantage of clipping the OFDM samples at low clipping level (hard clipping) is

getting better improvement in PAPR. The clipping technique at low amplitude values

causing distortion in the received signal and serious degradation in the SER

performance, so it is important to choose the clipping level carefully.

As shown in Figure 4.14 and Table 4.4, the SER degradation is increased as

the order of modulation schemes is increased and the CR is decreased. This is because

of the duration of the symbol is increased when using high order modulation scheme

to map the input data into the carriers. The high peaks in OFDM samples are very rare

so choosing appropriate CR is crucial to get the improvement in PAPR and avoid any

degradation in the SER performance.

Table 4.4 SER degradation of normal OFDM-IEEE 802.16e signal at moderate CRs with different modulation schemes

Mod. scheme

ModerateCR

SER degradation at 10-4

SER degradation at compared to the

normal OFDM-4QAM 10-6

4-QAM

compared to the normal OFDM-4QAM

0.4 1.5 0.98

16-QAM 0.7 8.6 8.2

64-QAM 1.2 9.9 8.9

256-QAM 1.9 10.2 9.1

140

Figure 4.15, 4.16, 4.17, and 4.18 shows the PSD of the clipped OFDM-

IEEE802.16e signal with various CRs from 0.2 to 1.2 for different modulation

schemes. In Figure 4.15, at CR of 0.2, the out-of-band noise emission power is only

16 dB lower than the signal power.

However at high CR of 1.06, it is easy to note that the spectral sidelobes are

now at least 30 dB lower than the signal mainlobe. As shown in the PSD graphs

below, the symbol that is mapped using low order modulation schemes (such as 4-

QAM and 16-QAM) can be clipped at lower CR than higher order schemes (such as

128-QAM and 256-QAM).

To summarize, the clipping technique causes out-of-band distortion that is

increased as the CR is decreased. The high order modulation schemes with high bit

loading per symbol are more vulnerable to high spectral splatter than lower schemes

especially when using low values of CR (hard clipping).

The appropriate definition of the clipping level is very important to mitigate

the noise emission power, but cannot eliminate the out-of-band radiation power. To

suppress the spectral splatter caused by clipping technique, the filtering after clipping

is necessary.

Actually it is difficult to expect the values of the high peaks in OFDM

samples, because they are variables for each OFDM symbol. By long observation of

the amplitude of OFDM symbols, appropriate selection of the clipping level can be

achieved. In the next section, the clipping and filtering technique will be discussed in

details.

141

(a)

(b)

Figure 4.15 PSD of clipped OFDM-IEEE 802.16e signal with 4-QAM at various

CRs of (a) 1.06, (b) 0.2

142

(a)

(b)

Figure 4.16 PSD of clipped OFDM-IEEE 802.16e signal with 16-QAM at various CRs of (a) 2.1, (b) 0.6

143

(a)

(b)

Figure 4.17 PSD of clipped OFDM-IEEE802.16e signal with 64-QAM at various

CRs of (a) 2.5, (b) 0.8

144

(a)

(b)

Figure 4.18 PSD of clipped OFDM-IEEE 802.16e signal with 256-QAM at

various CRs of (a) 3.2, (b) 1.6

145

4.4 OUT-OF-BAND RADIATION

Clipping is a nonlinear process and may cause significant in-band distortion, which

degrades the SER performance, and out-of-band noise, which reduces the spectral

efficiency. Filtering after clipping can reduce the spectral splatter but may also cause

some peak regrowth.

Figures 4.19 and 4.20 show the effect of clipping and filtering on the

performance of a conventional IEEE802.11g-OFDM-256QAM system. In this system

the out-of-band noise emission power is 40 dB lower than the signal power. As

shown in Figure 4.19 and after clipping the OFDM-256QAM signal at low CR of 1.8,

the spectral sidelobes is now only 25 dB lower than the signal mainlobe. It is easy to

note the out-of-band distortion caused by clipping, the filtering after clipping has the

ability to mitigate this problem.

As shown in Figure 4.20 the spectral sidelobes after applying filtering process

is now 37 dB lower than the signal mainlobe. This proves that filtering after clipping

has great ability to suppress the spectral splatter caused by clipping. However the

degradation in the performance of the SER that is generated from the in-band

distortion cannot be solved by the filtering process. This problem will be solved by

proposing recovering method of the clipped peaks at the receiver.

Clipping the OFDM signal at CR of 2.1 will make the spectral sidelobes to be

only 20 dB lower than the signal power. However after applying the filtering, it is

easy to note that the spectral sidelobes are now 28 dB lower than the signal mainlobe

as shown in Figure 4.22. The 1 dB in-band ripple caused by the FIR filtering may

boost the power of some subchannels while suppressing others. However, with

forward error correction (FEC) coding (which is not studied in this simulation) across

the subchannels, the effect of these ripples should be negligible. In normal OFDM-

IEEE802.16e the out-of-band noise emission power is 30 dB lower than the signal

power as shown in Figure 4.21.

146

2.36 2.37 2.38 2.39 2.4 2.41 2.42 2.43 2.44 2.45 2.46

-85

-80

-75

-70

-65

-60

-55

-50

-45

-40

Frequency (GHz)

Pow

er/fr

eque

ncy

(dB

/Hz)

Power Spectral Density Estimate via Welch

Conventional OFDM-256QAMClipped OFDM-256QAM (CR=1.1)

Figure 4.19 PSD of Normal and Clipped OFDM-IEEE802.11g Signals with

256-QAM

2.36 2.37 2.38 2.39 2.4 2.41 2.42 2.43 2.44 2.45 2.46-90

-85

-80

-75

-70

-65

-60

-55

-50

-45

-40

Frequency (GHz)

Powe

r/fre

quen

cy (d

B/Hz

)

Power Spectral Density Estimate via Welch

Conventional OFDM-256QAMClipped and filtered OFDM-256QAM

Figure 4.20 PSD of Normal and Clipped-Filtered OFDM-IEEE802.11g Signals

with 256-QAM

Normal OFDM-256QAM

Clipped &filtered OFDM-256QAM

Normal OFDM-256QAM

Clipped OFDM-256QAM (CR= 1.8)

37 dB

25 dB

147

2.236 2.237 2.238 2.239 2.24 2.241 2.242 2.243 2.244-60

-55

-50

-45

-40

-35

-30

-25

-20

Frequency(GHZ)

Ampl

itude

Frequency response of the transmitted signal

Conventional OFDM-256QAMClipped OFDM-256QAM (CR=0.6)

Figure 4.21 PSD of the normal and clipped OFDM-IEEE 802.16e signal with

256-QAM

2.236 2.237 2.238 2.239 2.24 2.241 2.242 2.243-60

-55

-50

-45

-40

-35

-30

-25

-20

Frequency(GHZ)

Am

plitu

de

Frequency response of the transmitted signal

Conventional OFDM-256QAMClipped and filtered OFDM-256QAM

Figure 4.22 PSD of the normal and clipped-filtered OFDM-IEEE 802.16e signal with 256-QAM

Normal OFDM-256QAM

Clipped OFDM-256QAM (CR= 2.1)

Normal OFDM-256QAM Clipped & filtered OFDM-256QAM

20 dB

28 dB

148

4.5 IN-BAND DISTORTION

The in-band distortion causes degradation in SER because of the distortion in the

shape of OFDM signal. Filtering cannot solve this problem because it related to lost

data in the clipped original signal. The envelope of OFDM signal suffers from high

fluctuation between the low and high peaks.

This fluctuation becomes higher as the order of modulation scheme increases.

The definition of clipping level needs long observation of the OFDM samples to

decide the appropriate CR. Moreover in any proposed solution to improve the

performance of OFDM system, clipping OFDM signal at low CR will restrict any

improvement in SER performance.

4.5.1 Error performance of the clipped passband OFDM signal

As shown in Figures 4.23, the in band distortion can degrade SER seriously when

clipping the digital OFDM signal directly. It is clear that there is no improvement in

SER until SNR of 25 dB because of using low CR of 2.2. However the degradation in

SER can be decreased dramatically when clipping the oversampled real valued

passband OFDM signal at the same low CR.

If the digital OFDM signals are clipped directly, the resulting clipping noise

will all fall in-band and cannot be reduced by filtering. To address this serious

problem, the OFDM signal is oversampled by a factor of 8. Then, the real-valued

passband samples are clipped at different CRs depends on the order of the utilized

modulation scheme. In this section, the effects of clipping the digital and real valued

passband OFDM signal directly on the performance of SER will be investigated at

different CRs and for various modulation schemes.

149

5 10 15 20 25 30 35 40 45

10-3

10-2

10-1

100

SNR (dB)

SER

Normal OFDM-256QAMClipped digital OFDM (CR=2.2)Clipped passband OFDM (CR=2.2)Clipped digital OFDM (CR=3.1)Clipped passband OFDM (CR=3.1)

Figure 4.23 The effect of in-band distortion on SER performance of OFDM-DVB-T-

256QAM system

4.5.2 EVM of the clipped passband OFDM signal

EVM is far greater than SER. In the case of high SNR, SER is nearly equal to zero

which could not fully characterize signal distortion of system. Obviously, it is

incapable to pursuit perfect system, while EVM still has high enough value which

contains more information and could characterize the imperfection of system. It is

important to investigate EVM of the clipped digital and passband OFDM signal to

confirm the advantage of clipping the passband OFDM signal over clipping the digital

signal. As shown in Figure 4.24 the EVM of the clipped passband signal is smaller

than EVM of clipped digital OFDM signal.

150

8 10 12 14 16 18 20 22 24

2

4

6

8

10

12

14

16

18

20

SNR (dB)

EVM

(%)

Normal OFDM without clippingClipped passband OFDM (CR=2.1)Clipped digital OFDM (CR=2.1)

Figure 4.24 EVM of normal, clipped passband and clipped digital OFDM-DVB-T- 256QAM

This emphasizes the ability of clipping the passband OFDM signal to mitigate

the in-band distortion and improve the SER performance despite using low CRs. In

any QAM mapping scheme, the size of the constellation points indicates the difficulty

the receiver faces in correctly recovering the data. Therefore the recovered OFDM

signal with high order scheme 256-QAM has large EVM at all SNRs. Table 4.5 lists

the EVM of normal, clipped passband, and clipped digital OFDM-DVB-T signals.

At SNR of 12 dB, EVM is dropped from 15.6% in clipped digital OFDM-

256QAM signal to 10.2% in the clipped passband signal, whereas it is only 5.6% in

normal (unclipped) signal. This is because of clipping the digital OFDM signal

directly causes serious in-band distortion that cannot be solved by filtering. Therefore

clipping the real valued passband OFDM signal can reduce the in-band distortion and

reduce the degradation in the performance of SER.

151

It is important to follow this procedure of clipping technique in OFDM system

that employs large number of subcarriers and utilizes high order modulation scheme

such as DVB-T with OFDM-256-QAM.

Table 4.5 EVM percentages at different SNRs for various modulation schemes

SNR (dB)

EVM percentage of normal OFDM with:

EVM percentage of passband clipped

OFDM with:

EVM percentage of digital clipped OFDM with:

256-QAM

64-QAM

16-QAM

256-QAM

64-QAM

16-QAM

256-QAM

64-QAM

16-QAM

No clipping CR=2.1 CR=1.4 CR=0.8 CR=2.1 CR=1.3 CR=0.8

8 10.2 8.4 6.2 14.5 11.8 8.1 18.2 16.5 12.8

12 5.6 3.1 1.7 10.2 8.5 4.8 15.6 12.3 8.7

16 4.1 1.8 0 8.3 6.1 3.2 13.9 9.6 6.2

20 1.4 0.11 0 6.1 4.3 1.2 9.5 6.8 4.8

25 0.3 0 0 4.2 2.1 0.5 7.8 4.1 2.9

4.6 THE UTILIZATION PERCENTAGE IN MODEL (1)

AMCl in model (1) utilizes at least two modulation schemes or more in each OFDM

symbol transmission in order to modulate the data onto subcarriers.

152

These schemes in each tested modes are chosen based on the calculated SER.

according to the rules of utilization in model (1), AMCl gives the chance to all

available modulation schemes to be utilizes at SNRs below 8 dB. However, as the

SNR increases the priority is given to the higher order schemes to be utilized.

In other words, the utilization percentage of low order modulation schemes is

high at low SNR, and then this percentage decreases dramatically as the value of SNR

increases. However, the utilization percentage of 256-QAM is increased all the time as

the value of SNR increases as shown in Figure 4.25.

5 10 15 200

10

20

30

40

50

60

70

80

90

100

SNR (dB)

Util

izat

ion

Per

cent

age

(Up)

%

4-QAM16-QAM64-QAM128-QAM256-QAM

Figure 4.25 The utilization percentage of modulation schemes in model (1)

It is important here to note that the rules of utilization percentage is different

based on the distance of users from the base station. In other words, these rules are

based on the sudden improvement in SER performance. It is essential to recall that the

CR definition mechanism updates the clipping level of each schemes based on the

conditions of the channel.

153

It is crucial to monitor a large number of transmitted OFDM frames in order to

find out the average value of utilization percentage of schemes in all tested modes.

Table 4.6 lists the percentage of utilization the modulation schemes in some tested

modes of model (1). The values of SNRs are classified into three groups namely low,

moderate, and high SNR. AMCl in each group has different rules of utilizing the

modulation scheme.

Table 4.6 Utilizations percentages of modulation schemes in model (1)

SNR threshold Modulation schemes

256 QAM

128 QAM

64 QAM

16 QAM

4 QAM

SNRlow< SNR≤ SNR 18 mod 26 26 25 5

SNRmod< SNR≤ SNR 73 high 16 9 2 0

SNRhigh 100 < SNR 0 0 0 0

Note: SNRlow = 0 dB, SNRmod =8 dB, and SNRhigh

=20 dB

According to the percentages in Table 4.6, the utilization percentage in model

(1) in all verified OFDM systems can be defined as follows:

( )

(4.7) 100)()(

)()()SNRSNRSNR(

416

64128256modlow ×

++

++=≤<

QAMPQAMP

QAMPQAMPQAMPP UU

UUUU

where Up is the utilization percentage of modulation scheme in one transmitted

OFDM symbol. The utilization percentage of the modulation schemes at SNR greater

than the SNRlow and less than or equal to the SNR

mod

( ) 100

)()(5)(5

)(54

201)SNRSNRSNR(

4)

16)64

128256

modlow ×

+

++

+

=≤<

QAMsub

QAMsubQAMsub

QAMsubQAMsub

P

NNN

NN

U

154

At SNR greater than SNRmod and less than or equal SNR

high

( )100

)(

)(29

121)SNRSNRSNR(

64

128256highmod ×

+

+=≤<

−

−−

QAMsub

QAMsubQAMsubP N

NNU

At SNR greater than SNR

high

( )[ ] 1001)SNRSNR( 256high ××=< −QAMsubP NU

More details and results about the selection policy and Utilization percentage

in each tested modes of model (1) for all verified OFDM based wireless systems will

be investigated in the next chapter.

4.7 THE UTILIZATION PERCENTAGE IN MODEL (2)

Unlike the utilization rule in model (1), AMCl in model (2) utilizes one or two

modulation schemes as maximum option to map the data onto subcarriers. As

mentioned in section 3.10.3, the decision will be made to select the modulation

scheme based on estimated value of SNR, and then based on the improvement in the

performance of SER the number of utilized modulation schemes can be defined. The

selection policy in this model tries to maintain the error rate stable and under the

target value of SER.

This means that the utilization percentage of any selected modulation scheme

increases gradually as the value of SNR increases and then AMCl will start utilizing

the adjacent order of modulation scheme with small percentage before discarding the

low order scheme from mapping process. In other words, two adjacent order of

modulation schemes can be utilized together at some SNRs based on the improvement

in SER. the utilization percentage of any modulation scheme in model (2) starts from

small value, goes to maximum value and then drops again to small value as shown in

Figure 4.26.

155

5 10 15 20 250

10

20

30

40

50

60

70

80

90

100

SNR (dB)

Util

izat

ion

Perc

enta

ge (U

p) %

4-QAM16-QAM64-QAM128-QAM256-QAM 16-QAM

& 64-QAM

128-QAM & 256-QAM

64-QAM & 128-QAM

4-QAM & 16-QAM

Figure 4.26 The utilization percentage of modulation schemes in model (2)

In order to calculate the utilization percentage of each modulation scheme in

the tested modes of model (2), long observation of each subcarrier in each transmitted

OFDM symbol should be carried out. The utilization percentage of the modulation

schemes at SNR greater SNRlow and less than or equal to SNRhigh

than in model (2)

can be calculated as follows:

( )[ ] (4.8) 100)()SNRSNRSNR( 21highlow ×+=≤< −− QAMMPQAMMPP UUU

where the order of modulation scheme M2 is greater than M1. The SNRlow is equal to

0 dB and SNRhigh

is equal to 22 dB.

In the selection policy of model (2), it is difficult to classify the SNR threshold

into three major groups (high, moderate, and low) because of the dependence of this

policy on the values of both SNR and SER. in other words, at each SNR value AMCl

utilize different set of modulation schemes based on the sudden improvement in SER.

156

Therefore, it is appropriate to classify SNRs into numerous groups in which

one or two modulation schemes are utilized together (based on SER) to modulate the

subcarriers in one OFDM symbol. After monitoring the utilization percentage of

modulation schemes in modes D and E, Tables 4.7 and 4.8 lists the averaged

utilization percentage in model (2).

Table 4.7 Utilization percentages of modulation schemes in model (2) with low CR

Mod. scheme

SNR (dB)

2-5 6-7 8-10 11-13 14-15 16 17-19 20-21 >21

4QAM 100 25 0 0 0 0 0 0 0

16QAM 0 75 100 28 0 0 0 0 0

64QAM 0 0 0 72 100 16 0 0 0

128QAM 0 0 0 0 0 84 100 10 0

256QAM 0 0 0 0 0 0 0 90 100

Table 4.8 Utilization percentages of modulation schemes in model (2) with high CR

Mod. scheme

SNR (dB)

2-5 6-7 8-10 11-13 14-15 16 17-19 20-21 >21

4QAM 100 4 0 0 0 0 0 0 0

16QAM 0 96 100 18 0 0 0 0 0

64QAM 0 0 0 82 100 12 0 0 0

128QAM 0 0 0 0 0 88 100 8 0

256QAM 0 0 0 0 0 0 0 92 100

157

Based on the percentages in Table 4.7 and 4.8, Table 4.9 lists the equations of

the utilization percentage of various modulation schemes in model (2) at low CR:

Table 4.9 Utilization equations at various SNRs in model (2) with low CR

SNR threshold Up

5dBSNRSNRlow ≤< equation

( )[ ] 1004 ×= −QAMPP UU

[ ] 100)(1 4 ××= QAMsubP NU

dB 7SNRdB 5 ≤< ( )[ ] 100)( 164 ×+= −− QAMPQAMPP UUU

[ ] 100)(24)(251

164 ×+= QAMsubQAMsubP NNU

dB 01SNRdB 7 ≤< [ ] 100)( 16 ×= −QAMPP UU

[ ] 100)(1 16 ××= QAMsubP NU

dB 13SNRdB 10 ≤< ( )[ ] 100)( 6416 ×+= −− QAMPQAMPP UUU

[ ] 100)(4)(51

164 ×+= QAMsubQAMsubP NNU

dB 51SNRdB 13 ≤< [ ] 100)( 64 ×= −QAMPP UU

[ ] 100)(1 64 ××= QAMsubP NU

dB 16SNRdB 15 ≤< ( )[ ] 100)( 12864 ×+= −− QAMPQAMPP UUU

[ ] 100)(22)(3251

12864 ×+= QAMsubQAMsubP NNU

dB 91SNRdB 16 ≤< [ ] 100)( 128 ×= −QAMPP UU

[ ] 100)(1 128 ××= QAMsubP NU

dB 21SNRdB 19 ≤< ( )[ ] 100)( 256128 ×+= −− QAMPQAMPP UUU

[ ] 100)(23)(2251

12864 ×+= QAMsubQAMsubP NNU

SNRSNRhigh < [ ] 100)()SNRSNR( 256high ×=< −QAMPP UU [ ] 100)(1)SNRSNR( 256high ××=< QAMsubP NU

158

Whereas, the equations of the utilization percentage of the modulation

schemes in model (2) at high CR are listed in Table 4.10:

Table 4.10 Utilization equations at various SNRs in model (2) with high CR

SNR threshold Up

5dBSNRSNRlow ≤< equation

( )[ ] 1004 ×= −QAMPP UU

[ ] 100)(1 4 ××= QAMsubP NU

dB 7SNRdB 5 ≤< ( )[ ] 100)( 164 ×+= −− QAMPQAMPP UUU

[ ] 100)(3)(41

164 ×+= QAMsubQAMsubP NNU

dB 01SNRdB 7 ≤< [ ] 100)( 16 ×= −QAMPP UU

[ ] 100)(1 16 ××= QAMsubP NU

dB 13SNRdB 10 ≤< ( )[ ] 100)( 6416 ×+= −− QAMPQAMPP UUU

[ ] 100)(18)(7251

164 ×+= QAMsubQAMsubP NNU

dB 51SNRdB 13 ≤< [ ] 100)( 64 ×= −QAMPP UU

[ ] 100)(1 64 ××= QAMsubP NU

dB 16SNRdB 15 ≤< ( )[ ] 100)( 12864 ×+= −− QAMPQAMPP UUU

[ ] 100)(21)(4251

12864 ×+= QAMsubQAMsubP NNU

dB 91SNRdB 16 ≤< [ ] 100)( 128 ×= −QAMPP UU

[ ] 100)(1 128 ××= QAMsubP NU

dB 21SNRdB 19 ≤< ( )[ ] 100)( 256128 ×+= −− QAMPQAMPP UUU

[ ] 100)(9)(101

12864 ×+= QAMsubQAMsubP NNU

SNRSNRhigh < [ ] 100)()SNRSNR( 256high ×=< −QAMPP UU

[ ] 100)(1)SNRSNR( 256high ××=< QAMsubP NU

159

4.8 SUMMARY

The effects of some parameters such as number of OFDM subcarriers, cyclic prefix,

zero padding, and clipping ratio on the performance of OFDM system are investigated

in details. The significance of definition an appropriate value of CR in clipping

technique is studied in this chapter. The results confirm the importance of proposing

updating mechanism of CR in order to control the percentage of the clipped OFDM

samples and then avoid any degradation in SER performance.

Some recommendations are suggested in this chapter to mitigate or eliminate

the effects of the two serious problems out-of-band radiation and in-band distortion

that caused by clipping technique. The CR definition mechanisms in both proposed

models are discussed with more details. The distribution policy that AMCl follows to

utilize the modulation scheme at all SNRs is investigated. In addition the effect of

updating mechanism in AMCl on defining the utilization percentage in each OFDM

symbol transmission is studied and listed in tables.

The SNR thresholds of AWGN for the conventional selection policy of AM in

normal OFDM system are defined according to SER of 10-5

and listed in Table 4.1.

Based on theses thresholds the decision about the individual modulation scheme in

conventional selection policy of AM is made. The modulation schemes in models (1)

and (2) will not be selected based on theses threshold values. However these threshold

values will be used to make comparison between the conventional selection policy and

policy in proposed modes.

CHAPTER V

THE PERFORMANCE OF AMCl IN OFDM BASEDWIRELESS SYSTEMS

5.1 INTRODUCTION

In this chapter, the algorithm AMCl will be validated and evaluated in three OFDM

based wireless systems namely IEEE 802.11g, IEEE 802.16e, and 4G. The results of

the tested modes in both models will be compared with the performance of normal

OFDM system that employs the conventional modulation selection policy. The most

important issue in this chapter is investigating the ability of AMCl to utilize the

appropriate mode and the modulation scheme that meets the requirements of channel

conditions.

In fact it is not fair to make any comparison between the tested modes, because

of each mode utilize different number of modulation scheme. However, it is essential

to investigate the ability of each tested mode to provide the verified OFDM system

with the preferable performance that it needs. The validation and evaluation of AMCl

in all tested OFDM systems will cover a detailed study of the performance of some

performance metrics such as SER, PAPR, and system throughput. The expected

performance of AMCl in both models is offering OFDM system with low PAPR, high

data throughput, and comparable SER compared to normal OFDM system.

161

5.2 THE SELECTION POLICY OF AMCl IN MODEL (1)

Model (1) offers a new selection policy of choosing the modulation schemes in AM to

map the data onto the carriers. Eight modes with five, four, and three modulation

schemes are tested in this model. The common concept in these proposed modes is

utilizing the high order modulation schemes together with the low order modulation

schemes especially at low SNR values. The percentage of using the different

modulation schemes at constant SNR will be controlled by the SER value. The

proposed model (1) introduces the clipping technique to solve the PAPR problem and

combines it with the modulation selection policy to improve the performance of the

OFDM system.

The combination of these two techniques will produce an algorithm that is

called AMCl. The clipping technique in AMCl algorithm will act as a controller of the

percentage of utilizing the modulation schemes at all SNRs. The controlling mission

can be achieved by appropriate definition of the clipping ratio (CR) which depends on

the order of modulation scheme. The CR will be updated periodically to meet the SER

after each successful symbol transmission.

This mission can be done by define a low CR (hard Clipping) for the low order

modulation schemes and quite high value for high order modulation schemes,

therefore the SER value will be kept between (0,r4

) (as discussed in Chapter III). This

means that all available modulation schemes will be participated to map the input data

with different percentage especially at constant low SNRs. This algorithm takes the

advantages of the two techniques and exploits them to improve the SER performance,

reduce the PAPR, and enhance the data rate in many applications of OFDM system.

To understand how this algorithm can improve the SER performance, it will be

validated in three OFDM based wireless systems.

162

a. IEEE802.11g

Tables 5.1 to 5.6 show the percentage of the modulated subcarriers in modes (A), (B),

(G), (H), and (I) at different SNR values using different order of modulation schemes.

At low SNRs both high and low order modulation schemes are utilized to map the

input data onto carriers, but as the SNR value is increased, the majority of the symbols

will be mapped using the highest order modulation scheme such as 128-QAM, and

256-QAM. As listed in Table 5.1, the proposed selection policy in mode (A) utilizes

all five modulation schemes in mapping process at all SNRs equal or below 8 dB.

Beyond this SNR the policy of AMCl algorithm will start discarding the low

order modulation schemes to avoid any wasting in the system bandwidth due to

utilizing low bit loading scheme. Until SNR of 20 dB the AMCl will utilize at least

two or more modulation schemes. Beyond 20 dB mode (A) will utilize the highest

order modulation scheme which is 256-QAM in mapping process. In other words the

AMCl algorithm will ensure to give the majority of utilizing percentage to the high

order schemes and discard the low order schemes from mapping process as the SNR is

increased. In the same time AMCl algorithm will keep the SER performance under

accepted value which depends on the tested mode.

The proposed AMCl algorithm shows ability to enhance the data rate of the

OFDM-IEEE802.11g system by controlling the percentage of using the modulation

schemes to map the input data onto the carriers by a careful selection of the value of

clipping ratio and assign the appropriate value of the SER to each modulation scheme

at constant SNR. Varying the thresholds of SER will change the utilization percentage

of each modulation scheme as shown in case (2) of mode (A) that is listed in Table

5.2. The proposed modes that utilize high order schemes will offer better enhancement

in the data rate than those that utilize lower schemes.

163

As shown in Table 5.1, at SNR equals to 5 dB, the OFDM symbols were

modulated using all five modulation schemes with equally percentage approximately,

with some majority percentage which was given to the high order modulation scheme

256-QAM. At 8 dB the majority 53% of the transmitted OFDM subcarriers were

modulated using the high order modulation schemes 128-QAM, and 256-QAM.

However at 12 dB which is the threshold value of 4-QAM, 100% of the transmitted

subcarriers were modulated using modulation schemes with order higher than the

order of 4-QAM. The same thing happens at 18 dB and 23 dB which are the threshold

value of 16-QAM, and 64-QAM respectively. The distribution percentages of

modulation schemes at all SNRs show enhancement in the data rate of the tested

system for all tested modes in model (1).

For example in Table 5.4, at SNR of 8 dB the proposed mode (G) will utilize

16, 64, and 256-QAM to modulate the OFDM symbol instead of utilizing the low

order scheme 4-QAM. Such utilization will enhance the system throughput

dramatically. Based on the data listed in below tables, it is possible to expect that the

tested modes which include 128-QAM or 256-QAM such as modes (A), (B), and (G)

can introduce SER performance less than the performance of normal OFDM with low

order modulation schemes such as BPSK, 4-QAM and 16-QAM. However the SER

performance of all tested modes in model (1) is better than the performance of normal

OFDM with high order schemes such as 64-QAM, 128-QAM, and 256-QAM because

of utilizing the high order schemes together with the low order schemes with different

percentages.

Moreover the tested modes which include the modulation scheme 64-QAM

such as (H) and (I) is expected to offer better SER performance compared to normal

OFDM with 64-QAM. Actually it is difficult to interpret theses data in below tables

without analyzing some important aspects in OFDM system such as the SER

performance, PAPR, and system throughput. In the next sections all theses aspects of

all tested modes of model (1) will be discussed in details.

164

Table 5.1 Percentages of modulated subcarriers in mode (A) of OFDM- IEEE 802.11g system (case 1)

SNR (dB) Utilization Percentage (%)

256-QAM 128-QAM 64-QAM 16-QAM 4-QAM

2 18 13 21 19 29

5 29 12 20 23 16

8 41 12 13 25 9

12 58 10 22 10 0

18 88 12 0 0 0

20 99 1 0 0 0

23 100 0 0 0 0

Table 5.2 Percentages of modulated subcarriers in mode (A) of OFDM- IEEE 802.11g system (case 2)

SNR (dB) Utilization Percentage (%)

256-QAM 128-QAM 64-QAM 16-QAM 4-QAM

2 0 0 0 39 61

5 0 0 9 43 48

8 0 3 43 47 7

10 8 29 53 10 0

12 28 51 17 4 0

18 76 22 2 0 0

20 97 3 0 0 0

23 100 0 0 0 0

165

Table 5.3 Percentages of modulated subcarriers in mode (B) of OFDM- IEEE 802.11g system

SNR (dB) Utilization Percentage (%)

256-QAM 64-QAM 16-QAM 4-QAM

2 18 19 25 38

8 34 30 19 17

12 61 26 13 0

18 89 11 0 0

20 98 2 0 0

23 100 0 0 0

Table 5.4 Percentages of modulated subcarriers in mode (G) of OFDM- IEEE 802.11g system

SNR (dB) Utilization Percentage (%)

256-QAM 64-QAM 16-QAM 4-QAM BPSK

2 5 22 29 39 5

5 20 21 23 28 8

8 27 29 21 23 0

12 40 23 22 15 0

18 64 25 11 0 0

20 94 6 0 0 0

23 100 0 0 0 0

Table 5.5 Percentages of modulated subcarriers in mode (H) of OFDM- IEEE 802.11g system

SNR (dB) Utilization Percentage (%)

64-QAM 16-QAM 4-QAM BPSK

2 28 43 25 4

5 44 38 18 0

8 58 42 0 0

12 87 13 0 0

14 99 1 0 0

16 100 0 0 0

166

Table 5.6 Percentages of modulated subcarriers in mode (I) of OFDM- IEEE 802.11g system

SNR (dB) Utilization Percentage (%)

64-QAM 16-QAM BPSK

2 10 85 5

5 40 58 2

8 55 45 0

10 63 37 0

12 90 10 0 15 100 0 0

Based on long observation of the quality of the received OFDM signal at low

SNRs, it was noticed that the SER at some moments has small value even the channel

condition still without change or sometimes the transmitter still receiving wrong

estimation about the channel. Using SER as controller instead of SNR will give

OFDM system the chance to utilize these good moments to utilize higher order

modulation schemes instead of using the current low order scheme. In other words the

AMCl algorithm in model (1) will utilize the high order schemes when the quality of

SER is improved and it will select the best scheme to keep SER under accepted value.

Each modulation scheme will be assigned to predefined number of error bits in one

OFDM symbol. Each mode in model (1) has different values of error bits.

Table 5.7 shows the values of error rate that are defined for each modulation

schemes in mode (A). To ease the explanation of the switching mechanism between

the utilized modulation schemes, the SER will be represented as the number of error

bits in one OFDM symbol. Based on the calculated SER in the last successful symbol

transmission, the decision will be made to switch the modulation schemes or keep it

without change. If there is no error in the received subcarrier, 256-QAM will be

selected as mapping schemes. If the SNR value is low, the decision will be made to

define low CR (hard clipping), whereas if the SNR is high, the CR is high (soft

clipping).

167

Definition the clipping level is very important to define the order of the next

candidate of mapping process. This is because of SER depends on the value of CR for

each modulation scheme. The appropriate definition of the CR is crucial to get the

advantage of clipping technique without degrading the SER or at least keeping the

SER between (0, r4

) to give the chance to all modulation schemes to be utilized in the

mapping process especially at low SNRs.

Table 5.7 SER switching values of modulation selection policy in mode (A)

SER Total number of error bits in one OFDM subcarrier Modulation scheme

0 0 256-QAM

r 1 1 128-QAM

r 2,3 2 64-QAM

r 4,5 3 16-QAM

r ≥ 6 4 4-QAM

Figure 5.1 shows the proposed selection policy in mode (A) that can switch

between the modulation schemes based on the calculated SER after each successful

symbol transmission. At SNR of 12 dB, if the total number of error bits in one OFDM

symbol are greater than or equal to 0 and less than 1 the decision will be made to

select 256-QAM to be the mapping scheme for the next symbol transmission, whereas

if they are greater than or equal to 1 and less than 2, the mapping scheme 128-QAM

will be chosen.

However, if they are greater than or equal to 2 and less than 4, AMCl

algorithm will select 64-QAM to modulate the next symbol. These values of SER

must be updated based on the selected mode. The CR and SER is working together to

control the selection policy and each one will affect on the other. In other word, based

on the value of SER the modulation scheme will be selected and based on this selected

scheme the clipping level will be defined. The high order scheme 256-QAM is utilized

only when the channel condition is good, whereas if the SER performance starts

degradation the AMCl algorithm will switch the mapping process to lower scheme

(such as 64-QAM or 128QAM).

168

Figure 5.1 The distribution policy of modulation schemes in the proposed mode (A) at SNR=12 dB

b. IEEE 802.16e

The proposed modulation selection policy in modes (F) and (G) of model (1) gives the

chance to all available modulation schemes to be used at low SNRs. In Table 5.8 all

five modulation schemes in mode (F) are being utilized with different percentages at

SNR below 8 dB. As the SNR is increased the AMCl algorithm will give the priority

to the high schemes and discard the low order schemes. Between SNRs 12 dB and 22

dB, there must be at least two modulation schemes to be used to map the input data.

The same observations can be seen in tested mode (G) as tabulated in Table 5.9. The

only different between modes (F) and (G) is that utilizing 128-QAM in mode (F)

instead of 64-QAM in mode (G). This will give mode (F) the ability to enhance the

data rate at all SNRs, whereas mode (G) will introduce better SER performance. All

data in these tables must be interpreted by analyzing the OFDM performance in terms

of SER, system throughput, and PAPR. All these aspects will be discussed later in the

next sections.

64-QAM 256-QAM 128-QAM

16-QAM

169

As mentioned before, the proposed selection policy can prove its ability to

enhance the data rate by using the high order modulation schemes such as 256-QAM

and 128-QAM to map the input data onto carriers at low SNRs as shown in Table 5.8

and 5.9.

In Table 5.9, at SNR equals to 8 dB (which is the threshold of BPSK in the

conventional selection policy of AM as listed in Table 4.1), 45% of the transmitted

subcarriers in one OFDM frame were modulated with the high order modulation

scheme 256-QAM, 15% with 64-QAM, 25% with 16-QAM and 15% of them with 4-

QAM. This means 100% of the transmitted subcarriers were modulated at 8 dB with

modulation schemes have order higher than the BPSK.

In addition, at 12 dB which is the threshold of 4-QAM, 100% of the

transmitted subcarriers were modulated with modulation schemes have order higher

than 4-QAM. At 18 dB, which is the threshold of 16-QAM, also all of the transmitted

symbols were modulated with modulation schemes have order higher than 16-QAM.

Table 5.8 Percentages of modulated subcarriers in mode (F) of OFDM- IEEE 802.16e system

SNR (dB) Utilization Percentage (%)

256-QAM 128-QAM 16-QAM 4-QAM BPSK

2 8 45 13 19 15

5 23 33 15 21 8

8 37 26 19 18 0

12 50 29 21 0 0

18 95 5 0 0 0

20 99 1 0 0 0

22 100 0 0 0 0

170

Table 5.9 Percentages of modulated subcarriers in mode (G) of OFDM- IEEE 802.16e system

SNR (dB) Utilization Percentage (%)

256-QAM 64-QAM 16-QAM 4-QAM BPSK

2 17 35 4 30 14

5 30 25 5 34 6

8 45 15 25 15 0

12 52 38 10 0 0

18 97 3 0 0 0

20 99 1 0 0 0

22 100 0 0 0 0

c. Fourth Generation

In the two tested modes (F) and (G), all available modulation schemes can be utilized

to modulate the OFDM symbols especially at Low SNRs below 8 dB. Compared to

the normal OFDM that applies the conventional modulation selection policy, only one

modulation scheme can be utilizes which is BPSK. With AMCl algorithm OFDM

system can utilize more than one modulation schemes when the SNR is constant

except the SNRs that are more than 20 dB as listed in Tables 5.10 and 5.11.

The goal of the new selection policy is giving the chance to the high order

modulation schemes to modulate the OFDM symbols at low SNRs and keep the SER

value under the accepted value. This value depends on the tested mode. The SER

switching value of selection the modulation schemes in mode (F) is totally different

from the defined values in mode (A) due to utilizing different modulation schemes.

171

Table 5.10 Percentages of modulated subcarriers in mode (F) of OFDM- 4G system

SNR (dB) Utilization Percentage (%)

256-QAM 128-QAM 16-QAM 4-QAM BPSK

2 2 12 35 42 9

5 14 19 41 23 3

8 18 28 42 12 0

12 33 30 32 5 0

18 74 26 0 0 0

20 98 2 0 0 0

23 100 0 0 0 0

The distribution policy of the modulation schemes that are utilized to modulate

the OFDM symbols in one OFDM frame in mode (F) is listed in Table 5.10. At SNR

equals to 8, 18 dB which are the threshold values of the modulation schemes BPSK,

and 16-QAM respectively, 100% of the transmitted OFDM subcarriers were

modulated using modulation schemes with order higher than BPSK, and 16-QAM.

However, at 12 dB, 95% of the transmitted subcarriers were modulated using

modulation schemes with order higher than 4-QAM. From the previous, it is easy to

note that the data rate of 4G system is enhanced especially at low SNRs. It is easy to

note that the data rate is enhanced dramatically at low SNRs as shown in the proposed

mode (G) in Table 5.11.

At SNR equals to 5 dB, the OFDM symbols were modulated using all

available modulation schemes especially at low SNRs. The percentage of using these

schemes will be controlled as mentioned before by the SER which is calculated from

the last successful symbol transmission. At 5 dB, 18% of the subcarriers were

modulated using the high order modulation scheme 256-QAM, but the majority of the

OFDM symbols (33% of the transmitted subcarriers) were modulated with the low

order modulation schemes 4-QAM. Only 3% of the transmitted OFDM subcarriers

were modulated using the lowest order modulation scheme BPSK.

172

100% of the transmitted subcarriers were modulated at 8 dB with modulation

schemes have order higher than the BPSK. Also at 12 dB which is the threshold of 4-

QAM (refer to Table 4.1), 96% of the transmitted subcarriers were modulated with

modulation schemes have order higher than 4-QAM. At 18 dB, 100% of the

transmitted subcarriers were modulated with modulation schemes have order higher

than 16-QAM.

Table 5.11 Percentages of modulated subcarriers in mode (G) of OFDM-

4G system

SNR (dB) Utilization Percentage (%)

256-QAM 64-QAM 16-QAM 4-QAM BPSK

2 6 13 37 39 5

5 18 21 25 33 3

8 33 13 26 28 0

12 40 26 30 4 0

18 76 24 0 0 0

20 99 1 0 0 0

23 100 0 0 0 0

Figure 5.2 shows the percentage of utilizing the high order modulation scheme

256-QAM in the three verified OFDM based wireless systems. At all SNRs, IEEE

80216e has the highest utilizing percentage of 256-QAM, and 4G system comes

second. Reference to the number of data subcarriers, IEEE802.16e has the largest

number of data subcarriers that is 720, whereas 4G has 128 data subcarriers, and IEEE

802.11g comes third with only 48 data subcarriers as listed in Table 3.1. Because of

256-QAM has the highest constellation points among the other utilized schemes, so

more bits can be carried over data subcarriers. In other words, increasing the utilizing

percentage of 256-QAM in IEEE802.16e will increase its ability to exploit the large

number of data subcarriers. This shows that AMCl can respond to the number of data

subcarriers in OFDM systems by increase the utilization percentage of the high order

modulation schemes. These results also prove the ability of AMCl algorithm in all

tested modes in model (1) to enhance the data rate at all SNRs.

173

2 8 12 18

SNR (dB)

Figure 5.2 Utilization percentages of 256-QAM in the verified OFDM systems

Refer to Table 3.5, the AMCl algorithm uses the CR updating mechanism to

define the value of clipping level for all utilized modulation scheme at each symbol

transmission. As explained before in chapter III, this mechanism defines the degree of

clipping of OFDM samples at all SNRs to keep the SER performance under an

accepted value. This accepted value of SER depends on the tested mode. In addition

this mechanism controls the utilization percentage of all modulation schemes. It

ensures utilizing of all schemes at low SNRs (usually less than 8 dB) and discarding

low order schemes as the SNR is increased. It avoids the toggle utilization between

only two high modulation schemes such as 128QAM and 256QAM at low SNRs. For

more details refer to Table 3.6 that lists the definition of CR for all utilized modulation

schemes in mode (A) at all SNRs.

Util

izat

ion

Perc

enta

ge (%

)

20

10

40

30

80

90

100

70

60

50

IEEE

802

.16e

4G

IEEE

802

.16e

IEEE

802

.11g

IEEE

802

.11g

4G

IEEE

802

.16e

IEEE

802

.11g

4G 4G

IEEE

802

.11g

IEEE

802

.16e

174

5.3 THE SELECTION POLICY OF AMCl IN MODEL (2)

The selection policy in model (2) will be developed by using the SNR and SER

together to choose the appropriate modulation scheme. The order of the modulation

scheme will be selected based on the SNR. However the percentage of using this

scheme will be based on the SER. At each constant SNR, two modulation schemes

will be utilized together with different percentage to modulate the OFDM symbols.

The value of CR will manage the percentage of using the utilized modulation

schemes. It is essential to define appropriate value of the clipping level for each

modulation scheme.

The definition of CR in model (2) depends only on the order of modulation

scheme. Unlike model (1), the CR in model (2) is constant (high or low) for each

modulation scheme as shown in Table 5.12. The OFDM signal all the tested modes in

model (2) will be clipped at two value of CR, the low (hard) and high (soft) CRs. This

is because of the selection policy in model (2) chooses the best modulation scheme

based on SNR. At each constant SNR, there are one or two (in maximum) modulation

schemes to be utilized to map the data onto carriers. This means that the modulation

scheme will not be chosen if the received SER is above the accepted value. Therefore

there is no need to update the value of CR after each symbol transmission and this will

decreased the complexity of the proposed model (2).

Table 5.12 Definitions of CRs in model (2)

Mode Target

SER

CR

value

Modulation Schemes

256-QAM 128-QAM 64-QAM 16-QAM 4-QAM

D 10 Low -3 3.4 3.0 2.6 1.8 1.1

10 High -4 3.8 3.2 2.9 2.2 1.5

E 10 Low -3 3.5 NA 2.7 2.0 1.3

10 High -5 4.2 NA 3.3 2.6 1.9

Note: NA refers to those modes that do not utilize this modulation scheme. NA: Not Applicable

175

a. IEEE.802.11g

Two modes (D) and (E) are validated in IEEE802.11g. As in model (1), the clipping

technique will be used to reduce the PAPR in model (2). Modes (D) and (E) will be

verified at two defined values of the CR (hard and soft). The AMCl algorithm should

keep the SER performance under the target value. To achieve this, AMCl must decide

at which SNRs mode D and E can utilize two modulation schemes. In addition, based

on the SER the AMCl will define the percentage of utilizing each modulation scheme.

Tables 5.13 and 5.14 list in details the percentage of distribution policy of

utilized modulation schemes in modes (D) and (E) to map the data onto the carriers to

generate the OFDM symbols. At each SNR the proposed AMCl algorithm will decide

the possibility of utilizing one or two modulation schemes without causing any

degradation in the SER performance.

The utilization percentage of these schemes will be decided based on the value

of SER. In Table 5.13, at SNR of 6 dB and with soft CR the AMCl algorithm in mode

(D) chooses two modulation schemes (4-QAM and 16-QAM) to modulate the OFDM

symbols. Only 5% of the transmitted subcarriers are modulated using 4-QAM and

95% of them are modulated using 16-QAM. However at SNR of 7 dB, AMCl will

increase the percentage of utilizing 16-QAM to become 98% with keeping SER under

the target value which is 10-4

.

As a rule in model (2) the percentage of utilizing the high order modulation

schemes is increased compared to the percentage of the low order modulation schemes

when using soft clipping ratio. The SER performance of mode (D) with soft CR is

better than it with hard CR, whereas mode (E) with soft CR has the best SER

performance among all other tested cases. Two reasons stand behind this improvement

in SER, the first one is not utilizing the high order scheme 128-QAM in mode (E) and

the second reason is using high CR that will decrease the amount of clipped peaks in

OFDM symbol.

176

Table 5.13 Percentages of modulated subcarriers in mode (D) of OFDM- IEEE802.11g system

Note Utilization

Percentages (UP

Utilization Percentages (U )

at Low CRs P

Utilized Modulation Schemes ) at High

CRs M-QAM SNR

Selection policy is based on SER and

SNR. Up

100

is controlled

by CR

100 4QAM 2-5

75 25 95 5 16QAM 4QAM 6

82 18 98 2 16QAM 4QAM 7

100 100 16QAM 8-10

71 29 75 25 64QAM 16QAM 11

81 19 90 10 64QAM 16QAM 12

100 100 64QAM 13-15

79 21 91 9 128QAM 64QAM 16

100 100 128QAM 17-19

88 12 95 5 256QAM 128QAM 20

93 7 98 2 256QAM 128QAM 21

100 100 256QAM >22

Table 5.14 Percentages of modulated subcarriers in mode (E) of OFDM- IEEE802.11g system

Note Utilization

Percentages (URPR) at Low CRs

Utilization Percentages (URPR)

at High CRs

Utilized Modulation

Schemes M-QAM

SNR

Selection policy is based on SER and

SNR. URpR is controlled

by CR

100 100 4QAM 2 -5

71 29 93 7 16QAM 4QAM 6

84 16 98 2 16QAM 4QAM 7

100 100 16QAM 8-12

94 6 96 4 64QAM 16QAM 13

100 100 64QAM 14-19

92 8 96 4 256QAM 64QAM 20

96 4 99 1 256QAM 64QAM 21

100 100 256QAM >22

177

5.4 VALIDATION OF AMCl IN MODEL (1)

5.4.1 SER Performance

a. IEEE801.11g

Despite the AMCl algorithm utilizes high order modulation schemes at low SNRs and

employs the clipping technique, the performance of SER in the tested modes (A) and

(B) in model (1) is better than normal OFDM-IEEE802.11g system that employs

conventional selection policy (Hanzo model), with modulation schemes 128-QAM,

and 256-QAM. The SER curves of modes (A) and (B) start below probability of 10-1

at SNR less than 10 dB, whereas they are above 10-1

in normal OFDM.

The SER performance of mode (B) is better than normal OFDM with 128-

QAM and 256-QAM at all SNRs. In mode (A) the SER performance of is better than

normal OFDM with 128-QAM below SNR of 20 dB, whereas it is better than normal

OFDM with 256-QAM at all SNRs. The distribution (modulation selection) policy

that is employed in AMCl algorithm is standing behind this improvement in SER

performance especially at low SNRs.

Utilizing the high order modulation schemes together with low order schemes

with different percentages that are controlled by SER and CR will offer SER

performance better than normal OFDM with high order schemes such as 64QAM,

128-QAM, and 256-QAM. In Figure 5.3 at SNR of 18 dB, 88% modulated subcarriers

in mode (A) were mapped using 256-QAM and 12% using 128-QAM (refer to Table

4.1). The effect of utilizing two modulation schemes can be noticed in the SER

improvement of mode (A) compared with normal OFDM with 256-QAM and even

with 128-QAM. In other words, mapping 12% of OFDM symbols using 128-QAM

can reflect to better improvement in the SER performance of mode (A) at 18 dB

compared to normal OFDM with 256-QAM.

178

At 20 dB most of the transmitted symbols (99%) in mode (A) were mapped

using 256-QAM, whereas only 1% of them were mapped using 128-QAM. This 1% of

symbols can improve the SER performance of mode (A) compared to normal OFDM

with 256-QAM. The mechanism in AMCl algorithm to define and update the values

of CRs of each modulation scheme proves its ability to achieve the advantage of

clipping technique in reduction the PAPR without affect the SER performance. This

can be noticed in Figure 5.3 when compare the SER performance of mode (A) with

the clipped OFDM system at high CR of 2.5. As mentioned earlier in this chapter the

appropriate definition of CR is very important to get the advantage of clipping

technique. Updating the value of CR at each new symbol transmission is essential to

meet the channel condition. The value of CR has classified into three categories, high,

moderate and low. Based on the order of modulation scheme and the estimated SNR,

the clipping level will be defined. In clipped OFDM system when using constant CR

(low, moderate or high) at all SNRs, the SER curve will be worse than the curve of

normal OFDM as shown in Figure 5.3.

In proposed mode (A) and (B), the CRs are always updated to meet the SNR

requirement, and this explains why their curves are better than normal or clipped

OFDM system. For example at SNR greater than or equal to 5 dB and less than 12 dB,

AMCl uses high CR (higher than 2.5) to clip the OFDM signal with 256-QAM.

However at SNR greater than or equal 12 dB and less than or equal 20 dB, AMCl will

use moderate CR (CR of 2.5), whereas at SNR higher than 20 dB, AMCl can use low

CR (CR of 1.6). Applying this mechanism of CR updating at each symbol

transmission shows its ability to mitigate the effect of clipping technique on SER

performance in the tested modes of model (1) as shown in Figure 5.3. The overlapping

between the SER curves of mode A (case 2) and mode B comes from the difference in

the utilization percentage of modulation schemes. According to the Utilization

percentages that are listed in Table 5.2 and 5.3, and at SNR of 18 dB, AMCl in mode

B utilizes 256-QAM to modulate 89% of subcarriers whereas in mode A (case 2) only

76% of transmitted subcarriers are modulated with 256-QAM. The same procedure

repeated at SNR of 20 dB. This leads to sudden improvement in SER of mode A (case

2) compared to mode B. Thus SER in mode A (case 2) at SNR equal to and greater

than 18 dB is better than SER of mode (B).

179

5 10 15 20 25 30 35 40

10-5

10-4

10-3

10-2

10-1

100

SNR (dB)

SER

Normal OFDM-256QAMClipped OFDM-256QAM (CR=2.8)Clipped OFDM-256QAM (CR=1.6)The proposed Mode A (case 1)The proposed Mode A (case 2)The proposed Mode B

Figure 5.3 SER performance of normal, clipped OFDM-IEEE802.11g signal with 256QAM, 128QAM and proposed modes (A) and (B)

It is important to define appropriate CR at each symbol transmission because it

will affect on the value of SER that will be used to select the order of modulation

scheme in the next symbol transmission. AMCl algorithm in all tested modes in model

(1) updates the value of CR frequently to meet the value of SNR. This means that

clipping level depends on the order of modulation scheme and the channel situation.

At low SNRs (in mode (C) usually between 2 dB and 8 dB) AMCl algorithm will

define high CR (soft clipping) for all utilized modulation scheme, whereas define

moderate or low CR (hard clipping) at high SNRs (in mode (C) usually higher than 8

dB).

The disadvantage of using constant CR at all SNRs can be noticed in Figure

5.4. Using constant low CR (lower than CR of 0.8) in OFDM with 64-QAM will

improve the PAPR but it will degrade the SER performance at all SNRs. Better SER

improvement can be obtained with constant high CR (higher than CR of 1.8) but the

price is high PAPR at all SNRs. AMCl in mode (C) will try to use the best value of

CR based on the current utilized modulation scheme and the estimated SNR to

achieve reasonable SER performance and better reduction in PAPR at all SNRs.

180

5 10 15 20 25

10-5

10-4

10-3

10-2

10-1

100

SNR (dB)

SER

Normal OFDM-64QAMClipped OFDM-64QAM (CR=2.2)Clipped OFDM-64QAM (CR=0.7)The proposed Mode C

Figure 5.4 SER performance of normal, clipped OFDM-IEEE802.11g signal with 64QAM and proposed mode (C)

Reference to Figures 5.3 and 5.4, Table 5.15 tabulates the SER improvement

in mode (A) at 10-2 and 10-3 SER level. The SER improvement at SER level of 10-2 is

3.8 dB, and 8 dB compared to the normal OFDM with 128, and 256-QAM

respectively, whereas the SER improvement is 1.3 dB, and 4.5 at 10-3. At 10-4 SER

level, there is no improvement in the SER performance of the proposed mode (A)

compared to normal OFDM with 128-QAM, whereas it is 3 dB compared to the

normal OFDM with 256-QAM. Also in mode (B) the improvement in SNR at SER

level of 10-2 is 10 dB, and 5.8 dB compared to the normal OFDM with 256, and

128QAM respectively. At 10-3 the improvement in the SER performance is 6 dB, and

2.8 dB compared to the normal OFDM with 256, and 128QAM respectively. At 10-4

SER level, the improvement is 2 dB and 5 dB compared to the normal OFDM with

128, and 256-QAM respectively. It is clear to notice the ability of the proposed mode

(C) to improve the SER performance of the OFDM-IEEE802.11g system. The

improvement in SER performance of mode (C) at 10-2, 10-3, and 10-4 SER level is 2.3,

1.8 dB, and 1.4 dB compared to the clipped OFDM-64QAM system at CR of 0.8.

181

Table 5.15 SER improvements at different SER levels of OFDM-IEEE 806.11g for tested modes (A),(B), and (C) in model (1)

Mode

SER improvement at 10-2

compared to the normal OFDM with (Hanzo model)

SER improvement at 10-3

compared to the normal OFDM with (Hanzo model)

256-QAM (dB) 64-QAM (dB) 256-QAM (dB) 64-QAM (dB)

Mode A 5.1 NA 2.7 NA

Mode B 7.1 NA 4.2 NA

Mode C NA 2.8 NA 1.4

Note: NA refers to those modes that do not utilize this modulation scheme. NA: Not Applicable

b. IEEE 802.16e

The improvement in the performance of SER of the proposed mode (F) as shown in

Figure 5.5 is better than the SER performance of the normal OFDM system with the

high order modulation schemes 128, and 256-QAM. However compared with the SER

performance of the normal OFDM that employs Hanzo model with 16-QAM, the

proposed mode (F) shows better SER performance below 9 dB. This because of

utilizing all modulation schemes at SNRs below 8 dB. In other words, utilizing low

order modulation schemes such as BPSK and 4-QAM with reasonable percentages

together with high order schemes will make SER performance of mode (F) better than

normal OFDM with 64-QAM, 128-QAM, and 256-QAM. The effect of updating

mechanism of CR can be noticed in mode (F). The AMCl algorithm proves its ability

to monitor the selection policy of modulation schemes and control their utilization

percentages. Despite employing clipping technique, this algorithm can offer mode (F)

with SER performance comparable to normal OFDM with 64-QAM and better than

normal OFDM with 128-QAM and 256-QAM. As shown in Figure 5.5, the SER

performance of mode (F) is better than normal OFDM with 128-QAM at SNRs below

8 dB due to utilizing low order modulation schemes such as BPSK, 4-QAM, and 16-

QAM together with other high order schemes in order to modulate the subcarriers.

182

Moreover, the improvement in the SER performance of mode (F) compared to

the normal OFDM with 256-QAM is 1.8 dB. At 10-4

5 10 15 20 25 30 35 40

10-6

10-5

10-4

10-3

10-2

10-1

100

SNR (dB)

SER

Normal OFDM-4QAMNormal OFDM-16QAMNormal OFDM-128QAMNormal OFDM-256QAMThe proposed Mode F

SER level the improvement in

the performance of SER is 4 dB compared to the normal OFDM with 128-QAM, and

it is 7 dB compared to the normal OFDM with 256-QAM.

Figure 5.5 SER performance of normal OFDM-IEEE 802.16e signal with 4, 16, 128, 256- QAM and proposed mode (F)

As shown in Figure 5.6, Utilizing low order modulation schemes such as

BPSK, 4-QAM, and 16-QAM at SNR below 8 dB (refer to Table 5.9) together with

other high schemes will improve the SER performance of mode (G). The updating

mechanism in AMCl defines the appropriate CR of each modulation scheme in order

to keep SER below 10-1 at SNR below 8 dB. It is easy to note this improvement in

SER performance especially at low SNR values compared to normal OFDM with 64,

and 256-QAM. Moreover the SER performance of mode (G) after employing the

AMCl algorithm is not only better than the performance of the normal OFDM with

64QAM, and 256-QAM but better than OFDM system with 16-QAM below SNR of 5

dB.

183

As explained before in mode (F), the distribution of modulation schemes in

AMCl algorithm and updating mechanism of CR for each schemes to meet the

channel conditions stand behind this improvement in SER performance. The low order

schemes BPSK, 4-QAM, and 16-QAM were utilized together with high order schemes

at SNRs below 14 dB (refer to Table 5.9), so the SER curve of mode (G) starts below

10-1

. Appropriate definition of CR with continues updating of it for each modulation

scheme has important effect to keep this curve under the curves of the clipped OFDM

systems with constant CRs at all SNRs.

5 10 15 20 25 30 35

10-6

10-5

10-4

10-3

10-2

10-1

100

SNR (dB)

SER

Normal OFDM-4QAMNormal OFDM-16QAMNormal OFDM-64QAMNormal OFDM-256QAMThe proposed Mode G

Figure 5.6 SER performance of normal OFDM-IEEE 802.16e signal with

4,16, 64, and 256-QAM and proposed mode (G)

Reference to Figure 5.6, Table 5.16 tabulates the improvement in SER

performance of mode (G) is more than 9 dB compared to the normal OFDM with 64-

QAM at the 10-2 SER level. But the improvement is 12 dB compared to the normal

OFDM with 256-QAM. It is only 2 dB compared with the normal OFDM with 16-

QAM. At 10-4 SER level the improvement in the performance of SER is 6 dB

compared to the normal OFDM with 64-QAM, and it is 9 dB compared to the normal

OFDM with 256-QAM. The SER performance of mode (G) is better than the SER

performance of mode (F) because of 128-QAM is not utilized as modulation scheme

in mode (G).

184

Table 5.16 SER improvements at different SER levels of OFDM-IEEE 802.16e for tested modes (F), and (G) in model (1)

Mode

SER improvement at 10-2

SER improvement at compared to the normal

OFDM (Hanzo model) 10-3

256-QAM (dB)

compared to the normal OFDM with (Hanzo model)

256-QAM (dB)

Mode F 1.8 1.3

Mode G 3.7 3.5

c. Fourth Generation

As shown in Figure 5.7, the SER performance of the two tested modes (F) and (G)

with five modulation schemes is better than normal OFDM that employs Hanzo model

with 256-QAM. It is easy to note this improvement in SER performance especially at

all SNRs. as discussed before in IEEE802.11g and IEEE802.16e, AMCl algorithm in

4G can play effective role in exploiting the system bandwidth and the subcarriers in

each symbol by utilizing the high order modulation schemes together with low order

schemes at low SNRs. it has a great ability to distribute the utilization percentages

among all available schemes and choose the best mode that meets the channel

conditions.

Updating the clipping level at each new symbol transmission based on the

SNR shows important function to minimize the effect of clipping technique on SER

performance. As shown in Figure 5.7 clipping OFDM signal at all SNRs with low

constant CR of 0.8 causes serious degradation in SER and keeps the SER curve above

10 P

-1P until SNR of 20 dB. With AMCl algorithm the CR can be updated to meet the

SNR, therefore the SER curve of modes (F) and (G) is superior compared to clipped

OFDM and better than normal OFDM with 256-QAM at all SNRs.

185

5 10 15 20 25 30 35

10-6

10-5

10-4

10-3

10-2

10-1

100

SNR (dB)

SER

Normal OFDM-256QAMClipped OFDM-256QAM (CR=2.8)The proposed Mode FThe Proposed Mode G

Figure 5.7 SER performance of normal, clipped OFDM-4G signal with

256-QAM and proposed modes (F) and (G)

In the proposed mode (F) with five modulation schemes, the improvement in

the SER performance compared to the normal OFDM with 256-QAM as shown in

Table 5.3 is 4 dB at the 10-2 SER level. But the improvement is 6 dB compared to the

clipped OFDM with 256-QAM with CR of 2.8. At 10-3

SER level the improvement in

the performance of SER is 3.5 dB compared to the normal OFDM with 256-QAM.

Although the OFDM signals in mode (C) are clipped, it is easy to note the

improvement in SER performance especially at low SNR values. The effect of

employing AMCl algorithm in mode (C) is clear as shown in Figure 5.8. The SER

curves of mode (C) is better than normal OFDM with 64-QAM. Modes (C) and (I) has

the same specifications except that mode (C) utilize 4-QAM instead of BPSK as in

mode (I). The utilization percentage in mode (C) shows that at SNR 12 dB

approximately 90% of the subcarriers were mapped using 64-QAM.

186

Despite of using clipping technique the difference between SER curve of mode

(C) and normal OFDM is clear. This is because of utilizing the low order scheme 16-

QAM to map 10% of symbols and define the appropriate CR for 64-QAM and 16-

QAM that meet SNR of 12 dB. Reference to Figure 5.8, the improvement in the SER

performance of mode (C) is more than 2.3 dB compared to the normal OFDM with

64-QAM at the 10-2

SER level as shown in Table 5.17.

2 4 6 8 10 12 14 16 18 20

10-5

10-4

10-3

10-2

10-1

100

SNR (dB)

SER

Normal OFDM-64QAMClipped OFDM-64QAM (CR=2.2)Clipped OFDM-64QAM (CR=1.3)The proposed Mode C

Figure 5.8 SER performance of normal OFDM-4G signal with 64-QAM and

proposed mode (C)

The improvement at 10-4 SER level is 4.5 dB compared to the clipped OFDM

with 64-QAM with CR of 1.3. At 10-4

SER level the improvement in the performance

of SER is 2.8 dB compared to the normal OFDM with 64-QAM.

187

Table 5.17 SER improvements at different SER levels of 4G-OFDM for tested modes (C), (F), and (G) in model (1)

Mode

SER improvement at 10-2

SER improvement at compared to the normal

OFDM with (Hanzo model) 10-3

256-QAM (dB)

compared to the normal OFDM with (Hanzo model)

64-QAM (dB) 256-QAM (dB) 64-QAM (dB)

Mode C NA 2.3 NA 2.1

Mode F 4 NA 3.5 NA

Mode G 5.6 NA 5.3 NA

Note: NA refers to those modes that do not utilize this modulation scheme. NA: Not Applicable

5.4.2 Improvement in PAPR

a. IEEE.801.11g

To investigate the effects of the proposed AMCl algorithm on PAPR in the tested

modes of model (1), it is essential to compare the PAPR distribution of the proposed

modes in model (1) to normal OFDM system with different modulation schemes. To

make this comparison more fair, the PAPR distribution of the proposed modes (A),

(B), and (C) is compared to the PAPR distribution of the normal OFDM with low

order modulation scheme such as 4-QAM.

AMC algorithm employs clipping technique in all tested modes, but the

clipping will be soft (using high CR) at low SNRs, whereas it is hard (using low CR)

at high SNRs. this means that the PAPR improvement at high SNRs will be better than

at low SNRs. it is important here to recall that the CR depends on the order of

modulation schemes and the channel condition. As shown in Figure 5.9, modes that

utilize 256-QAM such as (A) and (B) will offer reduction in PAPR less than modes

that do not utilize it such as (C).

188

Therefore the PAPR distribution of mode (C) is better than modes (A) and (B).

In addition the PAPR distribution of mode (B) is better than mode (A), because of

utilizing 128-QAM in mode (A) instead of 64-QAM in mode (B).

2 4 6 8 10 12 1410

-4

10-3

10-2

10-1

100

PAPR0(dB)

CC

DF(

Pr(

PA

PR

>PA

PR

0))

Conventional OFDM-256QAMConventional OFDM-4QAMThe proposed Mode AThe proposed Mode BThe proposed Mode C

Figure 5.9 CCDF of PAPR normal OFDM-IEEE802.11g signal with 256-QAM,

4-QAM and proposed modes (A), (B), and (C)

The PAPR improvement in mode (A) at the probability of 10-3 is 3.02 dB, and

1.6 dB compared to the normal OFDM with 256, and 4-QAM respectively. The best

improvement in the PAPR at the probability of 10-3

is achieved with the proposed

mode C. This improvement is 5.97 dB compared to the conventional normal OFDM

with 64-QAM, whereas it is 5.3 dB compared to the normal OFDM with 4-QAM as

shown in Table 5.18.

189

Table 5.18 PAPR improvements in OFDM-IEEE802.11g at probability of 10-3

modes (A), (B), and (C) in

Mode

PAPR reduction compared to the normal OFDM with:

256-QAM (dB) 64-QAM (dB) 4-QAM (dB)

Mode A 3.02 NA 1.6

Mode B 3.22 NA 1.8

Mode C NA 5.97 5.3

Note: NA refers to those modes that do not utilize this modulation scheme. NA: Not Applicable

b. IEEE 80216.e

OFDM-IEEE 802.16e system employs 720 data carriers which make this system

suffers from the largest PAPR among the other two verified systems. This will make

the mission of AMCl algorithm more difficult to choose the appropriate CR of each

utilized schemes especially at low SNRs.

The proposed mode (G) shows better improvement in PAPR than the proposed

mode (F), because of utilizing the high modulation scheme 128-QAM together with

256-QAM in mode (F). In other words at any value of SNR, AMCl algorithm in mode

F will use higher CR than it will use in mode (G).

The result of this behavior of AMCl algorithm in mode (F) is less PAPR

improvement than mode (G). Figure 5.10 shows the CCDF of the normal OFDM,

mode (F), and mode (G).

190

2 4 6 8 10 12 14 16

10-3

10-2

10-1

100

PAPR0(dB)

CCDF

(Pr(P

APR>

PAPR

0))

The proposed Mode FThe proposed Mode GNormal OFDM-BPSKNormal OFDM-256QAM

Figure 5.10 CCDF of PAPR for normal OFDM-IEEE802.16e signal with BPSK, 16, 64, 128, 256-QAM and proposed modes (F), and (G)

The best improvement in the PAPR is achieved with mode (G) which is 3.9 dB

at the probability of 10-3

compared to the normal OFDM with BPSK, whereas it is 6

dB compared to the normal OFDM with 256-QAM as shown in Table 5.19.

As mentioned before the proposed mode F shows quite low improvement in

the PAPR because of using high clipping ratio value to avoid the degradation in the

performance of the SER due to using the two high order modulation schemes 128, and

256-QAM.

Table 5.19 PAPR improvements in OFDM-IEEE802.16e at probability of 10-3

modes (F), and (G) in

Reduction in the PAPR at the probability of 10-3

Mode 256-QAM (dB) BPSK (dB)

3.8 1.7 Mode F

6 3.9 Mode G

191

c. Fourth Generation

compared to the normal OFDM with:

Figure 5.11 shows the PAPR distribution of the tested modes (B), (F), and (G) in

model (1) of 4G system. Because of mode (F) utilizes the high order scheme 128-

QAM instead of 64-QAM in mode (G), this will give AMCl algorithm more freedom

in mode (G) to clip the OFDM signal harder (using low CR) than signal in mode (F).

This interprets the best improvement of PAPR in mode (G). Mode (B) utilizes 4-QAM

at low SNR, whereas modes (F) and (G) utilize both BPSK and 4-QAM. This is the

reason of increase the probability of high peaks between 2 and 8 dB in mode (B).

2 4 6 8 10 12 14 16

10-3

10-2

10-1

100

PAPR0 (dB)

CC

DF

(Pr(

PA

PR

>PA

PR

0))

Normal OFDM-256QAMNormal OFDM-BPSKThe proposed Mode BThe proposed Mode FThe proposed Mode G

Figure 5.11 CCDF of PAPR for normal OFDM-4G signal with 256-QAM and proposed modes (B), (F), and (G)

In Figure 5.12, the PAPR improvement in mode C is 4.9 dB compared to

normal OFDM with 64-QAM and 3.5 dB compared to normal OFDM with 4-QAM.

The best improvement in PAPR among all tested modes of 4G system is noticed in the

proposed mode (C) as listed in Table 5.20. This is because of mode (C) does not

utilize neither 128-QAM nor 256-QAM.

192

Other tested modes (B), (F), and (G) show less improvement in PAPR because

of using the high order modulation scheme 256-QAM especially mode F that is using

the two high order modulation schemes 128, and 256-QAM. As explained before, the

modes that utilize high order modulation schemes cannot use low CR with these high

schemes especially at low SNRs. this gives priority to modes with low order

modulation schemes to be used in system that suffers from high PAPR.

2 4 6 8 10 12 14 16

10-3

10-2

10-1

100

PAPR0 (dB)

CCDF

(Pr(P

APR>

PAPR

0))

Normal OFDM-64QAMNormal OFDM-BPSKThe proposed Mode C

Figure 5.12 CCDF of PAPR for normal OFDM-4G signal with 64-QAM and

proposed mode (C)

Table 5.20 PAPR improvements in OFDM-4G at probability of 10-3

modes (B), (C), (F), and (G) in tested

PAPR reduction compared to the normal OFDM with:

Mode 256-QAM (dB) 64-QAM (dB) 4-QAM (dB) BPSK (dB)

4.1 NA 3.2 NA Mode B

NA 4.9 3.8 NA Mode C

3.1 NA NA 2.2 Mode F

4.5 NA NA 3.6 Mode G Note: NA refers to those modes that do not utilize this modulation scheme. NA: Not Applicable

193

5.4.3 Throughput Enhancement

a. IEEE.802.11g

Recall the definition of AMCl algorithm which is the combination of novel

modulation selection policy in AM and the clipping technique. The third goal that

should be achieved is enhancement the throughput of OFDM based wireless systems.

This goal can be fulfilled by the proposed selection policy in the tested modes of

model (1). The conventional modulation selection policy in AM (Hanzo model)

assigns only one modulation scheme to each group of SNRs as shown in Table 4.1.

This mechanism will keep the throughput of OFDM system constant within boundary

of each SNR group and system throughput curve will be like a stair as shown in

Figure 5.13. In the same figure the advantage of using the novel policy in the tested

modes (A) and (B) can be seen obviously. The drawn data in this figure is

interpretation of the subcarriers percentages that were listed in Tables 5.1, 5.2, and

5.3.

The selection policy in model (1) which is discussed before in section 5.1 can

enhance the data rate in OFDM-IEEE802.11g system by utilizing the high order

modulation schemes at low SNRs with the low order schemes and control the

percentages of this hybrid utilization using appropriate definition of the CR. The bit

rate in all tested modes of model (1) is not a fixed at constant SNR as in the

conventional selection policy of AM. In other word if bad channel condition still

without change for a long time or the transmitter receives wrong estimation about the

channel status, the conventional policy of AM will choose low order schemes and the

system throughput will be fixed at low data rate. However with the novel policy in

AMCl algorithm, the system throughput will be enhanced and it will not be fixed at

low data rate. It is clear that the enhancement in the bit rate of the proposed modes can

be achieved at all SNR values especially at low SNR values. This enhancement in the

throughput comes from using the high order modulation schemes such as 64, 128, and

256-QAM together with the low order modulation schemes at low SNRs.

194

The proposed mode (A) shows better enhancement in the data rate than the

proposed mode (B) especially at low SNRs, because of using 128-QAM in mode (A)

instead of 64-QAM in mode (B). The comparison between the throughput of the

proposed modes with novel selection policy and the normal OFDM system with

conventional selection policy is based on the AWGN switching thresholds, (refer to

Table 4.1) that are used in the conventional AM. The comparison shows superior

enhancement in the OFDM throughput of the proposed modes over the normal OFDM

system with the conventional selection policy at all SNRs. To calculate the data rate of

the OFDM-IEEE 802.11g system, refer to Table 3.1 and recall Equation 3.22. The

data rate of IEEE 802.11g with 256-QAM is

s

subbs T

NNR ×=

μs 4488×

=

= 96 Mbps

Mode (A) employs five modulation schemes which are 4-QAM, 16-QAM, 64-

QAM, 128-QAM, and 256-QAM. Recalling Equation 3.23 and referring to Table 5.1

the data rate of mode (A) (case1) in IEEE802.11g at SNR of 8 dB can be calculated as

follows

s

M

pm RUR ×= ∑1

= (0.41×96) + (0.12×84) + (0.13×72) + (0.25×48) + (0.09×24)

= 72.96 Mbps

For more details, Table 5.21 lists the data throughput of the tested modes (A)

(case1), (B), and (C) at different SNRs in IEEE 802.11g system.

Table 5.21 Data throughput of tested modes in IEEE 802.11g

Mode Mode A Mode B Mode C

SNR (dB) 2 12 18 2 12 18 2 12 18

Throughput (Mbps) 58.79 84.74 94.52 52.08 83.54 93.37 48.71 61.92 71.99

195

5 10 15 20 25 3010

20

30

40

50

60

70

80

90

100

SNR (dB)

Thro

ughp

ut (

Mbp

s)

Normal OFDM with conventional AMThe proposed Mode A (case 1)The proposed Mode A (case 2)The proposed Mode B

Figure 5.13 Throughput of normal OFDM-IEEE802.11g with conventional AM (Hanzo model) and proposed modes (A), and (B)

Table 5.21 proves the ability of the proposed modes (A), and (B) to enhance

the data rate at all SNRs especially at low SNR values. This is because of utilizing

high order modulation schemes such as 64-QAM, 128-QAM, and 256-QAM at low

SNRs. As a result of this enhancement in system throughput, the proposed modes in

model (1) offer good reduction in the required time to send the data.

As listed in Table 5.22, the required time to transfer one GB at SNR of 2 dB

with the proposed mode (A), (B), and (C) is four times less than the time required by

using the normal OFDM with the conventional selection policy. As the value of SNR

is increased, the required transmission time becomes the same for proposed modes

and the normal OFDM due to utilizing the same order of modulation schemes at all of

them. The proposed mode (A) shows the least required time to transfer the data,

because of using the high order modulation schemes 128-QAM, and 256-QAM.

196

Recall Equation 3.24 and using the calculated data rate of mode (A) in

IEEE802.11g to find out the required transmission time at SNR of 8 dB

ms R

DT =

Mbps96.72 MB1000 =

= 13.71 second

Table 5.22 Comparisons between the required transmission times in normal OFDM-IEEE 802.11g and proposed modes (A), (B), and (C) at different SNRs

Data size

Transmission time when using: SNR value (dB)

Mode A (second)

Mode B (second)

Mode C (second)

Normal OFDM with Conventional AM

(Hanzo model) (second)

1 GB

17.01 19.20 20.53 83.33 2

13.71 14.83 16.15 41.67 8

11.80 11.97 14.52 41.67 12

10.58 10.71 13.89 20.83 18

10.43 10.47 13.89 13.89 20

10.42 10.42 13.89 11.91 23

10.42 10.42 13.89 10.42 25

b. IEEE 802.16e

The conventional selection policy does not improve the data throughput at constant

SNR because of using only one modulation scheme based on AWGN switching

thresholds. However the proposed modes (F) and (G) with the new selection policy of

AM can provide a significant increment in throughput of OFDM system by utilizing

all modulation schemes especially at low SNRs. Table 5.23 lists the data throughput

of these tested modes at different SNRs.

197

Table 5.23 Data throughput of different modes in IEEE 802.16e

Mode Mode F Mode G SNR (dB) 2 12 18 2 12 18

Throughput (Mbps) 36.68 54.08 62.62 34.33 53.85 62.50

The two proposed modes (F), and (G) as shown in Figure 5.14, can really

introduce a huge enhancement in the system throughput compared to the normal

OFDM system that using the conventional selection policy at all SNRs below 25 dB.

Beyond this value of SNR the selection policy in AMCl algorithm in the tested modes

(F) and (G) will discard all modulation schemes that have order lower than the order

of 256-QAM. At SNR of 25 dB, the normal OFDM with conventional policy and the

proposed modes are with novel policy are using the same modulation scheme that is

256-QAM. The proposed mode (F) offers better increment in the data rate than the

proposed mode (G) especially at low SNRs, due to utilizing 128-QAM in mode (F)

instead of 64-QAM in mode (G). As a result of this, mode (F) can achieve better

saving in the required transmission time than the proposed mode (G) as tabulated in

Table 5.24 and 5.25.

5 10 15 20 25 30

10

20

30

40

50

60

SNR (dB)

Thro

ughp

ut (M

bps)

Normal OFDM with conventional AMThe proposed Mode FThe proposed Mode G

Figure 5.14 Throughput of normal OFDM-IEEE802.16e with conventional AM (Hanzo model) and proposed modes (F), and (G)

198

Table 5.24 Comparisons between the required transmission times in normal OFDM-IEEE 802.16e and proposed mode (F) at different SNRs

Data size

Transmission time when using: SNR value (dB) Proposed Mode (F)

(second)

OFDM with Conventional AM (Hanzo model)

(second)

1GB

27.26 127.07 2

24.85 127.07 5

18.49 63.49 12

15.97 31.76 18

15.90 21.16 20

15.88 18.14 23

15.88 15.88 25

Table 5.25 Comparisons between the required transmission times in normal OFDM and proposed mode (G) at different SNRs

Data size

Transmission time when using: SNR value (dB) Proposed Mode (G)

(second)

OFDM with Conventional AM (Hanzo model)

(second)

1GB

29.13 127.07 2

26.24 127.07 5

18.57 63.49 12

16.00 31.76 18

15.92 21.16 20

15.88 18.14 23

15.88 15.88 25

c. Fourth Generation

199

It is easy to note that the bit rate of normal OFDM that employs the conventional

modulation selection policy is increasing as the value of SNR is increasing. This

conventional policy assigns boundaries of SNRs for each modulation scheme in order

to keep the SER performance under the target value. Sometimes the SNR still constant

without change for period of time or the transmitted received wrong estimated SNR.

These entire aspects cause a constant throughput and make the conventional

policy of AM is not good choice to enhance the system throughput. The novel

selection policy in AMCl can avoid all these problems in conventional policy by

utilizing (with different percentage) all available modulation schemes especially at

low SNRs.

The novel selection policy is based on SER. The utilization percentage of these

schemes is controlled by mechanism of updating CRs at each symbol transmission.

Recall Equations 3.22 and 3.23 in chapter III and refer to Tables 5.10 and 5.11, the

data throughput of tested modes (F) and (G) can be calculated at different SNRs as

tabulated in Table 5.26.

Table 5.26 Data throughput of different modes in 4G

Mode Mode F Mode G

SNR (dB) 2 12 18 2 12 18

Throughput (Mbps) 417.71 766.87 968.99 413.91 756.43 939.85

As shown in Figure 5.15 the system throughput in tested modes (F) and (G) is

enhanced at all SNRs. The SER target value is different from mode to another

depends on the utilized modulation schemes in the chosen mode.

200

5 10 15 20 25 30

2

3

4

5

6

7

8

9

10

11x 10

8

SNR (dB)

Thro

ughp

ut (

bps)

Normal OFDM with conventional AMThe proposed Mode FThe proposed Mode G

Figure 5.15 Throughput of normal OFDM-4G with conventional AM (Hanzo model)

and proposed modes (F), and (G)

The AMCl algorithm in proposed modes (F) in 4G system shows its ability to

increase the data rate at all SNRs below 25 dB compared to the normal OFDM with

the conventional selection policy. Mode (F) has system throughput better than mode

(G) below 20 dB due to utilizing 128-QAM in mode (F) instead of 64-QAM in mode

(G).

Tables 5.27 and 5.28 show that the transmission time of the data (5 GB as

example) in mode (F) and (G) is four times less than the time required in the normal

OFDM at SNR of 2 and 5 dB. OFDM-4G system in mode (F) and (G) can provide

data throughput up to 1 Gbps when utilizing 256-QAM. This interprets using data

with size of 5 GB in all tested modes of 4G system in model (1).

201

Table 5.27 Comparisons between the required transmission times in normal OFDM-4G and proposed mode (F) at different SNRs

Data size

Transmission time when using: SNR value (dB) Mode F (second)

Normal OFDM with conventional AM (Hanzo model)

(second)

5 GB

11.97 40 2

8.71 40 5

6.52 20 12

5.16 10 18

5.01 6.67 20

5 5.69 23

5 5 25

Table 5.28 Comparisons between the required transmission times in normal OFDM-4G and proposed mode (G) at different SNRs

Data size

Transmission time when using: SNR value (dB) Mode G (second)

Normal OFDM with Conventional AM

(Hanzo model) (second)

5 GB

12.08 40 2

9.09 40 5

6.61 20 12

5.32 10 18

5.01 6.67 20

5 5.69 23

5 5 25

202

5.5 VALIDATION OF AMCL IN MODEL (2)

5.5.1 SER performance comparison

The SER performance of mode (D) with hard CR can be shown in Figure 5.16.

Despite all OFDM symbols are clipped hardly at low CR, the curve is kept under 10-3.

The SER performance of mode (D) with soft CR is kept under 10-4

at low SNRs with

some increment between 12 dB and 18 dB, because of using the high order schemes

64 and 128QAM at these SNRs which are below the SNR thresholds value of these

schemes.

This increment is caused by the clipping technique. This means that the novel

selection policy in model (2) can offer SER performance comparable to the normal

OFDM that employs the conventional AM when using high CR for all utilized

modulation schemes. The word (conventional AM) in all comparisons refers to the

conventional modulation selection policy that is discussed in section 2.5.4. This

conventional policy is known as Torrance model.

Clipping OFDM signal in mode (D) with low CR offers better improvement in

PAPR, whereas it degrade the SER performance when utilize the modulation schemes

16, 64, 128, and 256-QAM at low SNRs of 6, 11, 16, and 20 dB because of mapping

the majority of OFDM symbols using these schemes.

In order to solve this increment at these SNRs by increase the percentage of

mapping more symbols in one OFDM Frame with low order schemes. In this case the

SER performance at these SNRs will be improved but the price is decrease the system

throughput. Actually despite there is increment in SER at some SNRs but the SER

performance still accepted under the target value which equals to 10-3.

203

2 4 6 8 10 12 14 16 18 20 22 24

10-5

10-4

10-3

10-2

10-1

SNR (dB)

SER

Mode D with hard clipping (low CR)Mode D with soft clipping (high CR)

Figure 5.16 SER performance of mode (D) with high and low CRs

The proposed selection policy in model (2) as explained before utilize one or

two adjacent order of modulation schemes at each constant SNR in order to enhance

the system throughput at all SNRs. to improve the PAPR in proposed modes of model

(2), clipping technique is employed at two different CRs (high and low CR). The SER

performance of mode (E) is kept under the target value at all SNRs. The target value

of SER in mode (E) when using high CR is 10-5, whereas it is 10-3

at low CR as shown

in Figure 5.17.

The instability in SER curve at some value of SNRs of mode (E) comes from

utilizing high order modulation scheme with another low scheme to enhance the data

rate at that SNRs. Reference to Table 5.14, at SNR of 13 dB the high order scheme

64-QAM will be utilized with the low scheme 16-QAM in mapping process at

different percentage. The utilization percentage is controlled by SER which is affected

by the CR in the last symbol transmission. This explains why it is important to define

the clipping level carefully for each modulation scheme to achieve improvement in

PAPR without degrade the SER performance.

204

The next mission is to compare the SER performance of modes (D) and (E)

with the normal (non-clipped) OFDM system that employs the conventional AM.

2 4 6 8 10 12 14 16 18 20 22 24

10-6

10-5

10-4

10-3

10-2

10-1

SNR (dB)

SE

R

Mode E with hard clipping (low CR)Mode E with soft clipping (high CR)

Figure 5.17 SER performance of mode (E) with high and low CR

The SER performance in mode (D) with soft CR is better than the SER

performance with hard CR. SER is totally kept under the target value which is 10-4

.

The degradation in SER performance of mode (D) is due to two reasons. The first one

is utilizing high order schemes with low order schemes at some SNRs to enhance the

data rate. The second reason is using clipping technique to mitigate the effect of high

PAPR.

Despite mode (E) using clipping technique with soft CR, but it offers SER

performance comparable to SER performance of the normal OFDM with conventional

modulation selection policy as shown in Figure 5.18. However, the advantage of

using two modulation schemes at some constant SNRs could be notice later when the

system throughput is discussed in details.

205

It is easy to note that the SER performance in mode (E) is better than mode

(D). This is because of utilizing 128-QAM to map the data in mode (D). The SER

performance of mode (E) at SNRs between 10-12 dB, and between 16-18 dB is

comparable to SER performance of normal OFDM system with conventional selection

policy of AM.

The reason stands behind this improvement is using ZP, CP, 2N-IFFT, filtering

after clipping and some others suggestions to improve the OFDM performance as

discussed before in Chapter III.

8 10 12 14 16 18 20 22 24

10-7

10-6

10-5

10-4

10-3

10-2

10-1

SNR (dB)

SE

R

Normal OFDM with conventional AM & without clippingMode D with soft clipping (high CR)Mode E with soft clipping (high CR)

Figure 5.18 SER performances of the normal OFDM-IEEE802.11g signal with conventional AM (Torrance Model) and proposed modes (D) and (E) with high CR

b. Fourth Generation

Mode E employs the proposed AMCl algorithm that defines the values of CR beased

on the target value of SER.

206

Therefore the SER performance of the proposed mode (E) in model (2) at high

CR is kept under the SER target value which is 10-5

at most SNRs as shown in Figure

5.19. The SER performance of mode (E) with soft clipping is comparable to the SER

performance of normal OFDM with conventional modulation selection policy.

For example at SNR of 7 dB, the normal OFDM with the conventional

selection policy will utilize 4-QAM to modulate the OFDM symbols (refer to Table

4.1), whereas mode (E) utilized 4-QAM and 16-QAM together at different percentage.

As a result of employing this policy, the SER performance in mode (E) is comparable

to conventional selection policy of AM as most SNRs.

6 8 10 12 14 16 18 20 22 24 26 2810

-7

10-6

10-5

10-4

10-3

10-2

10-1

SNR (dB)

SE

R

Noral OFDM with conventional AM & without clippingMode D with soft clipping (high CR)Mode E with soft clipping (high CR)

Figure 5.19 SER performance of normal OFDM-4G signal with conventional AM (Torrance Model) and proposed modes (D) and (E)

207

5.5.2 PAPR reduction

a. IEEE802.11g

Clipping the OFDM signal at high clipping level (high CR) achieves PAPR

improvement less than clipping at low clipping level (low CR). However the price of

this improvement is degradation in SER. The degree of degradation in SER depends

on the order of modulation schemes.

In other words the OFDM symbols that are modulated using low order

modulation scheme such as 4-QAM can be clipped harder (using lower CR) than

those that are modulated using higher order schemes such as 64-QAM.

The proposed algorithm AMCl in model (2) employs clipping technique to

monitor the percentage of utilizing the modulation schemes by controlling the values

of SER. In addition clipping technique reduces the high PAPR in OFDM system.

Figures 5.20, 5.21, and 5.22 show the improvement in the PAPR at hard

clipping (low CRs) and soft clipping (high CRs) for all utilized modulation schemes in

the tested modes (D) and (E). The PAPR of the unclipped OFDM-256QAM signal in

Figure 5.20 is 14.2 dB.

When using low CRs of 2.9 and 2.2 the PAPR at the probability of 10-3

is only

11.8 dB and 10.6 dB respectively. The improvement in PAPR when using high CR of

3.8 is 0.41 dB. This means that for high CR the OFDM signal is unclipped, but as CR

decreases to zero, the peak and average power converge to 0 dB.

208

8 9 10 11 12 13 14 1510

-4

10-3

10-2

10-1

100

PAPR0(dB)

CC

DF(

Pr(

PAPR

>PA

PR

0))

Normal OFDM-256QAMClipped OFDM-256QAM (CR=3.8)Clipped OFDM-256QAM (CR=2.9)Clipped OFDM-256QAM (CR=2.2)

Figure 5.20 CCDF of PAPR for normal and clipped OFDM-IEEE802.11g signal with 256-QAM at high and low CRs

8 9 10 11 12 13 14 1510

-4

10-3

10-2

10-1

100

PAPR0(dB)

CCD

F(Pr

(PA

PR>P

APR

0))

Normal OFDM-128QAMClipped OFDM-128QAM (CR=3.2)Clipped OFDM-128QAM (CR=2.5)Clipped OFDM-128QAM (CR=2.0)Normal OFDM-64QAMClipped OFDM-64QAM (CR=2.9)Clipped OFDM-64QAM (CR=2.2)Clipped OFDM-64QAM (CR=1.8)

Figure 5.21 CCDF of PAPR for normal and clipped OFDM-IEEE802.11g signal with 128 and 64-QAM at high and low CRs

209

4 6 8 10 12 14 1610

-4

10-3

10-2

10-1

100

PAPR0(dB)

CCD

F(Pr

(PA

PR>P

APR

0))

Normal OFDM-16QAMClipped OFDM-16QAM (CR=2.2)Clipped OFDM-16QAM (CR=1.2)Normal OFDM-4QAMClipped OFDM-4QAM (CR=1.5)Clipped OFDM-4QAM (CR=0.6)

Figure 5.22 CCDF of PAPR for normal and clipped OFDM-IEEE802.11g with 16 and 4-QAM at high and low CRs

Table 5.29 shows in details the improvements in the PAPR of the two

proposed mode (D) in model (2) using different modulation schemes at different

values of CR.

The best improvement in the PAPR is achieved with the low order modulation

schemes such as 4-QAM, and 16-QAM because of the possibility of using hard CR in

these schemes.

The best reduction in PAPR in modes (D) and (E) is achieved with OFDM-

4QAM at low CR 0.6 at probability of 10-3 which is 7.37 dB as shown in Figure 5.22.

However such low value of CR cannot offer SER performance under 10-3

especially at

low SNRs below 8 dB.

210

Table 5.29 PAPR improvements compared to normal OFDM-IEEE 802.11g at probability of 10-3

Mode

in proposed modes (D) and (E)

Mode D Mode E

Modulation scheme

256 QAM

128 QAM

64 QAM

16 QAM

4 QAM

256 QAM

64 QAM

16 QAM

4 QAM

CR 3.8 3.2 2.9 2.2 1.5 4.2 3.3 2.6 1.9

PAPR imprvmnt 1.21 1.34 2.05 2.58 2.84 0.41 0.47 1.77 2.03

b. Fourth Generation

Figure 5.23 shows the improvement in PAPR in mode (E) that employs four

modulation schemes 256, 64, 16, and 4-QAM. The improvement in the PAPR is 2.7

dB when mode (E) utilizes 256-QAM. As explained before, the order of modulation

schemes plays a key role to define the value of CR. Using lower order schemes

increases the possibility of using lower CR. Therefore the best reduction in PAPR in

mode (E) that is 8.8 dB is achieved with 4-QAM because of using lower CR. However

the performance of SER will be degraded seriously at SNRs below 8 dB if CR of 0.6

is used to clip OFDM-4QAM signal.

As mentioned before the definition of CR in AMCl algorithm in model (2)

depends on the target value of SER. Therefore higher CRs are used to keep SER under

the accepted value. In 4G system, OFDM signal with 4-QAM is clipped at CRs of 1.5

and 1.9 in the tested modes (D) and (E) respectively. This introduces the necessity to

suggest solution that can offer possibility to clip OFDM signal at low CR without

degrade the SER performance seriously. In next chapter this solution will be discussed

in details.

211

4 6 8 10 12 14 16

10-3

10-2

10-1

100

PAPR0 (dB)

CC

DF

(Pr(

PA

PR

>PA

PR

0))

Normal OFDM with 256-QAMMPC OFDM with 256-QAMNormal OFDM with 4-QAMMPC OFDM with 4-QAM

Figure 5.23 CCDF of PAPR for normal and clipped OFDM-4G signal with 4-QAM and 256-QAM at different CRs

5.5.3 Data rate enhancement

a. IEEE.802.11g

Despite the AMCl algorithm in the tested modes (D) and (E) of model (2) is

employing the clipping technique at low and high CR, it can offer better enhancement

in the data rate at all SNRs as shown in Figures 5.24 and 5.25.

The best enhancement in the throughput is achieved in the tested mode D with

soft clipping (high CR). The proposed AMCl algorithm in model (2) defines constant

value of CR for each utilized modulation scheme.

Normal OFDM-256QAM

Clipped OFDM-4QAM (CR=0.6)

Clipped OFDM-256QAM (CR=3.9)

Normal OFDM-4QAM

212

The modulation scheme is selected to map the input data based on SNR and

the percentage of utilizing it will be controlled by SER that is calculated in the last

symbol transmission and depends on the value of CR. This proves the importance of

appropriate definition of the clipping level for each modulation scheme. Recall that at

each SNR, one or two modulation schemes will be utilized for mapping process.

Reference to Tables 5.10 and 5.11, using high CR (soft clipping) increases the

utilization percentage of the higher order modulation scheme. This means that the

tested modes with soft clipping (high CR) will achieve better enhancement in the

system throughput at all SNRs. in addition the tested modes that employs higher

modulation schemes at some SNRs will achieve higher data rates at that SNRs. The

proposed mode (D) shows better enhancement in the throughput of the OFDM system

than the proposed mode (E) between 10 dB and 20 dB, because of utilizing the high

order modulation schemes 64-QAM, and 128-QAM in mode (D) instead of using only

64-QAM as in mode (E).

The two proposed modes (D) and (E) show their ability to increase the data

rate at all SNRs. The two proposed modes (D) and (E) at low CR can offer better

enhancement in the throughput of IEEE802.11g system compared to the normal

(unclipped) OFDM that employs conventional modulation selection policy (Torrance

Model). The problem in the conventional modulation selection policy appears when

the channel conditions still without change for long time or receive wrong estimation

about that condition. This problem can be shown in Figures 5.24 and 5.25. The

throughput curve of normal OFDM that employs conventional selection policy

without clipping is constant at some SNRs. Moreover the proposed selection policy in

modes (D) and (E) shows its ability to enhance the data rate at all SNRs compared to

normal OFDM with conventional policy. It is clear that the curve of the proposed

modes (D) and (E) has constant value of data rate at some SNRs due to utilizing only

one modulation scheme at those SNRs. The throughput of mode (E) at SNR of 19 dB

is equivalent to throughput of normal OFDM with conventional policy (Torrance

Model) due to utilizing the same modulation scheme. Mode (E) utilizes 64-QAM

between SNR of 14 dB and 19 dB, whereas normal OFDM utilizes it between 19 dB

and 20 dB. However mode (D) offers higher throughput at SNR of 19 dB due to

utilizing 128-QAM.

213

To calculate the data rate of OFDM-IEEE 802.11g system, refer to the system

parameters that are listed in Table 3.1 and recall Equation 3.22. The data rate of IEEE

802.11g with 128-QAM is

s

subbQAMOFDMs T

NNR ×=− )128(

μs 4487×

=

= 84 Mbps

And the data rate when utilize 64-QAM is equal to:

μs 4486

)128(×

=− QAMOFDMsR

= 72 Mbps

Mode (D) employs five modulation schemes which are 4-QAM, 16-QAM, 64-

QAM, 128-QAM, and 256-QAM. By Recalling Equation 3.23 in chapter III and

referring to Table 5.10 the data rate of mode (D) in IEEE802.11g at SNR of 16 dB

when using high CR (soft clipping) can be calculated as follows

s

M

pm RUR ×= ∑1

= (0.09×72) + (0.91×84)

= 82.92 Mbps

Recall Equation 3.24 in Chapter III and using the calculated data rate of mode

(D) in IEEE802.11g at high CR to find out the required transmission at SNR of 16 dB

m

s RDT =

Mbps92.82 MB1000 =

= 12.06 second

This means that the novel selection policy in the proposed mode (D) of

IEEE80211g can send 1 GB at SNR of 16 dB in 12.06 sec, whereas this time is 20.83

sec in normal OFDM with conventional selection policy (Torrance Model).

214

5 10 15 20 25 3010

20

30

40

50

60

70

80

90

100

SNR (dB)

Thro

ughp

ut (M

bps)

Normal OFDM with conventional AM&without clippingMode D with hard clipping (low CR)Mode E with hard clipping (low CR)

Figure 5.24 Throughput of OFDM-IEEE802.11g with conventional AM

(Torrance Model) and proposed modes (E), and (D) with low CR

6 8 10 12 14 16 18 20 22 2410

20

30

40

50

60

70

80

90

100

SNR (dB)

Thro

ughp

ut (M

bps)

Normal OFDM with conventional AM&without clippingMode D with soft clipping (high CR)Mode E with soft clipping (high CR)

Figure 5.25 Throughput of OFDM-IEEE802.11g with conventional AM

(Torrance Model) and proposed modes (E), and (D) with high CR

215

Table 5.30 and 5.31 shows that the time required to send one Gbps using

modes (D) and (E) at low and high CRs is less than the time required to send the same

size of data using the normal OFDM with the conventional selection policy. The best

saving in the transmission time is also achieved in mode (D) with low CR. The

calculation of the transmission time of the proposed modes and the normal OFDM

system with the conventional adaptive modulation is based on the AWGN switching

thresholds (refer to Table 4.1) in the normal OFDM with conventional modulation

selection policy and at SER level of 10-5

.

Table 5.30 Comparisons between the required transmission times in normal OFDM-IEEE 802.11g and proposed mode (D) at different SNRs

Data size

Transmission time when using: SNR value (dB)

Mode D (High CR) (second)

Mode D (Low CR) (second)

Normal OFDM with Torrance Model

(second)

1GB

41.67 41.67 83.33 2-5

21.36 23.81 83.33 6

21.04 22.89 83.33 7

20.83 20.83 41.67 8-10

15.15 15.38 41.67 11

14.37 14.83 41.67 12

13.89 13.89 20.83 13-15

12.06 12.27 20.83 16

11.90 11.90 20.83 17-19

10.48 10.58 13.89 20

10.44 10.51 11.91 21

10.42 10.42 10.42 >25

216

Table 5.31 Comparisons between the required transmission times of normal OFDM-IEEE 802.11g and proposed mode (E) at different SNRs

Data size

Transmission time when using: SNR value (dB)

Mode E (High CR) (second)

Mode E (Low CR) (second)

Normal OFDM with Torrance Model

(second)

1GB

41.67 41.67 83.33 2-5

21.59 24.37 83.33 6

21.04 22.64 83.33 7

20.83 20.83 41.67 8-12

14.08 14.17 41.67 13

13.89 13.89 20.83 14-19

10.52 10.63 13.89 20

10.44 10.52 11.91 21

10.42 10.42 10.42 >25

The transmission time between SNRs of 2 dB and 5 dB is reduced by 2 times

only, whereas between 6 dB and 7 dB, the transmission time is 4 times less than the

time required in the normal OFDM system. This is because of using the high order

modulation schemes 16-QAM together with 4-QAM to modulate the OFDM symbols

at these SNRs.

In addition this saving in the transmission time can be seen at SNR values 11,

12, and 16 dB because of using the high order modulation schemes together with low

order modulation schemes such as (64-QAM with 16-QAM), (128-QAM with 64-

QAM), and (256-QAM with 128-QAM). This reduction or saving in the transmission

time is high at low SNRs and become less as the value of SNR is increased.

217

5.6 COST FUNCTION OF ALGORITHM AMCl

Recall Equation (2.47), the cost function of AMCl algorithm can be calculated in both

models (1) and (2). To get this function, the expected increment in the bit errors

divided by the increment in data throughput in each subcarrier must be found for two

successive tested modes.

For example, the cost function in transition between modes (A) and (B) in

model (1) of IEEE 802.11g and at SNR of 2 dB can be calculated as follows:

snsn

snsnsn bb

eec

,1,

,1,, −

−=

+

+

71.4879.58

35−−

=

198.0=

Whereas in the proposed model (2), the cost function of AMCl in the transition

between the tested modes (D) and (E) of IEEE 802.11g and at SNR of 18 dB is equal

to

snc , 99.7103.8412

−−

=

083.0=

The low complexity in algorithm AMCl can be noticed at the low values of the

cost function in the transition between the tested modes in both models. This value of

function decreases as the value of SNR increases because of improvement in SER

performance and increment in the utilization percentage of the higher order

modulation schemes.

218

5.6 SUMMARY

The proposed AMCl algorithm (the combination of the two novel models (1) and (2)

with the clipping technique) is validated in three known OFDM based wireless

systems namely IEEE 802.11g, IEEE 802.16e, and 4G. Each model in AMCl includes

a number of modes that utilize different number of modulation schemes.

The tested mode (A) in model (1) offers improvement in PAPR of 1.6 dB, and

3.02 dB compared to the normal OFDM-IEEE 802.11g with 4-QAM and 256QAM

respectively, whereas the improvement in mode (C) is 5.3 dB and 5.97 dB compared

to the normal OFDM with 4-QAM and 64-QAM respectively.

Mode (F) in IEEE 802.16e offers 1.7 dB and 3.8 dB as improvement in PAPR

compared to the normal OFDM with BPSK and 256-QAM respectively. The reduction

in PAPR in Mode (G) is in order of 3.9 dB and 6 dB. In fourth generation, mode (B)

shows improvement in PAPR of 3.2 dB, and 4.1 dB compared to normal OFDM with

BPSK and 256-QAM respectively. The SER improvement in IEEE 802.11g in mode

(A) and (B) is 2.7 dB and 4.2 dB respectively compared to normal OFDM that

employs Hanzo model with 256-QAM at probability of 10-3, whereas in IEEE

802.16e, modes (F) and (G) have got SER improvement of 1.3 dB and 3.5 dB

respectively. Mode (G) in fourth generation system offers 5.3 dB as an improvement

in SER at probability of 10-3

compared to normal OFDM with 256-QAM.

The data rate in IEEE 802.11g can be enhanced from 12 Mbps to 72.94 Mbps

in mode (A), whereas it can be enhanced to 67.43 Mbps in model (B) at SNR of 8 dB.

As result of this throughput enhancement, the required transmission time will be

reduced dramatically. For example in IEEE 802.16e, in mode (F) the required time to

transfer 1 Gbps at SNR of 5 dB is reduced from 127.07 second to 24.85 second, and

from 31.76 second to 15.97 second at SNR of 18 dB. The overall improvement in the

performance of the verified OFDM based wireless systems that were obtained due to

employing AMCl algorithm in the tested modes of model (1) is summarized in Table

5.32.

219

Table 5.32 Overall performance improvements in some tested modes of AMCl in model (1)

Mode

Comparison with Normal OFDM-256QAM with Hanzo model

SER Improvements

at 10-3

PAPR

SER level

Improvement at Probability of

10-3

Data

at SNR

Throughput Enhancement

at SNR

10 10-2 5 dB -3 2 dB 12 dB 20 dB

IEEE 802.11g

Mode A 5.1 2.7 3.0 4.9 3.5 1.3

Mode B 7.1 4.2 3.2 4.3 3.4 1.2

IEEE 802.16e

Mode F 1.8 1.3 3.8 4.7 3.4 1.3

Mode G 3.7 3.5 6.0 4.3 3.3 1.2

Fourth Generation

Mode F 4.0 3.5 3.1 4.7 3.4 2.0

Mode G 5.6 5.3 4.5 4.4 3.4 2.0

In model (2), mode (D) shows improvement in PAPR of IEEE 802.11g

system. In mode (D), when OFDM signal is clipped at CRs of 1.5 and 3.8, it offers

improvement of 2.84 dB, and 1.21 dB compared to the normal OFDM with 4-QAM

and 256QAM respectively with hard clipping ratio, whereas the improvement is 3.1

dB 1.6 dB and with low CRs of 1.1 and 3.4.

220

In mode (E), the SER value of IEEE 802.11g is kept under 10-3 when OFDM

samples with 4-QAM and 256-QAM are clipped at low CRs of 1.3 and 3.5, whereas

SER is kept under 10-4

with softly clipping at CRs of 1.9 and 4.2 respectively. The

SER curve of mode (E) is really comparable to the normal OFDM with conventional

selection policy (Torrance model) despite of clipping process. The PAPR

improvement in mode (E) is less than in mode (D) due to using higher CRs in mode

(E). These improvements are 2.03 dB and 0.41 dB at CRs of 1.9 and 4.2 compared to

normal OFDM with 4-QAM and 256-QAM respectively.

In mode (D) with hard clipping ratio the data rate is enhanced from 24 Mbps to

67.43 Mbps at SNR of 12 dB and enhanced to 69.59 Mbps with soft clipping ratio.

The required transmission time is reduced from 41.67 second to 14.37 second with

soft clipping ratio at 12 dB. Mode (D) offers better enhancement in IEEE 802.11g

throughput better than mode (E) because of utilizing 128-QAM. Table 5.33

summarizes the overall obtained improvement in the performance of the verified IEEE

802.11g system in both tested modes (D) and (E).

Table 5.33 Overall performance improvements in some tested modes of AMCl in model (2)

Syst

em

Mod

e

Improvement Comparison with Normal OFDM-256QAM with

Torrance Model

Throughput Enhancement Compared to Normal OFDM System with Torrance

Model

Target SER

PAPR at Prob. 10-3

SNR (dB)

(dB) 6 12 18 20

Low CR

High CR

Low CR

High CR

Low CR

High CR

Low CR

HighCR

Low CR

HighCR

Low CR

HighCR

IEEE

80

2.11

g D 10 10-3 3.7 -4 1.5 3.9 3.5 2.9 2.8 1.7 1.6 1.3 1.3

E 10 10-3 3.2 -5 0.4 3.8 3.4 2.0 2.0 1.4 1.4 1.3 1.3

221

Actually, it is not fair to make any comparison between the tested modes in the

same models, because they are utilizing a different number of modulation schemes.

However it is essential to investigate the ability of each mode to provide the verified

OFDM system with the best performance that it needs. Moreover the comparison

between the two proposed models can give a good vision of suitability of them in

some OFDM based wireless systems in terms of SER, PAPR, and data throughput.

Table 5.34

provides a comprehensive comparison between the two proposed models

of selection policy in adaptive modulation.

Table 5.34 Comparison between the two proposed modulation selection policy models

Comparison Model (1) Model (2) Modulation selection policy

Based on SER Based on SNR and SER

CR updating mechanism Defined based on SNR Defined based on target SER

Freedom in CR definition Can define three different values of CR to meet the channel condition

Can define only one value of CR that maintain SER under target value

Utilization percentage AMCl utilizes Two modulation schemes or more at SNRs below 20 dB

AMCl utilizes one or two modulation scheme as maximum option at all SNRs.

SER performance Comparable to normal OFDM without adaptive modulation

Comparable to normal OFDM with adaptive modulation

SER performance Stability Non stable Stable

Data throughput High enhancement in the data throughput at all SNRs below 20 dB compare to normal OFDM with conventional AM

Less enhancement in the data throughput compared to the proposed model (1)

PAPR improvement High improvement compared to normal OFDM system

Low improvement compared to model (1)

Suitability to OFDM application

More suitable to 4G and DVB-T in terms of data throughput and PAPR reduction.

More suitable to IEEE 802.11g and IEEE 802.16e in terms of SER performance.

CHAPTER VI

CONCLUSIONS AND FUTURE WORK

6.1 INTRODUCTION

This chapter concludes the presentation of the work by resuming the achieved results,

and directions for further studies are also indicated.

6.1 CONCLUSIONS

In order to solve the problems in the selection policy of AM that are related to fixed

and low throughput at most SNRs, two models of modulation selection policy are

proposed namely model (1) and model (2). Each model employs number of modes

that utilize different number of modulation schemes. These models are combined with

the CR updating mechanism to introduce an algorithm called Adaptive Modulation

and Clipping (AMCl).

The results of the tested modes in model (1) show the ability of AMCl to

reduce the PAPR and enhance the data rate of the OFDM system at all SNRs. The

updating mechanism of CRs in AMCl shows great ability to offer suitable distribution

in utilization all available modulation schemes at all SNRs. This ability can be noticed

in the SER performance of the tested modes in model (1).

223

The SER performance at SNRs below 8 dB is better than the SER performance

of the normal (unclipped) OFDM with high order modulation schemes such as 64-

QAM, and 128-QAM. However, the SER performance of the tested modes in model

(1) is better than normal OFDM with 256-QAM at all SNRs. Moreover the SER

performance of these modes is superior to the SER performance of the clipped OFDM

system. AMCl algorithm in model (1) shows better improvement in the PAPR

compared to the normal OFDM system with different modulation schemes. Moreover

the proposed modulation selection policy in model (1) offers an enhancement in the

throughput of the OFDM system at all SNRs compared to the normal OFDM that

employs the conventional selection policy of AM. As a result of this increment in the

data rate of the verified systems, the required time to transfer these data can be

reduced dramatically at all SNRs.

Despite of clipping the OFDM samples, AMCl algorithm in model (2) offers

reasonable SER compared to the normal OFDM system. Because of AMCl defines the

values of CR based on the target SER, the SER performance is comparable to the

normal (unclipped) OFDM with conventional selection policy especially when

clipping OFDM signal at high CR. The tested modes in model (2) have superior SER

performance compared to the SER performance of the clipped OFDM system. The

effectiveness of the selection policy in the proposed model (2) over the conventional

policy can be noticed in the throughput of the OFDM system that is enhanced at all

SNRs. This increment in the data rate comes from using two modulation schemes

together with different utilization percentage at most SNRs. Definition an appropriate

value of CR based on target SER is essential in model (2) to define the degree of

enhancement in the data rate. Results shows that clipping OFDM samples at low CR

causes increment in the utilization percentage of low order modulation scheme and

vice versa. All tested modes in model (2) offers huge enhancement in data throughput

when clipping OFDM samples at high CRs, whereas these modes offer less PAPR

improvement. The SER performance of model (2) is better than the SER performance

of model (1). This is because of AMCl in model (2) utilizes only one or two adjacent

order of modulation schemes (as a maximum option) that meet the values of SNR and

SER, whereas in model (1) two schemes or more are utilized at SNRs below 20 dB

with different percentages depends on SER.

224

Moreover AMCl in model (1) employs updating mechanism of CR that defines

and updates the values of CR based on estimated SNR, whereas in model (2) constant

value of CR is defined based on the target SER. All this reasons make the SER

performance of model (2) better than model (1) and comparable to normal OFDM

with conventional selection policy. As a result of the excellent performance of SER in

the tested modes in model (2), and because of the reciprocal relationship between

PAPR and SER, the data rate enhancement in model (1) is better than the

enhancement in model (2) at most SNRs.

AMCl algorithm in both models offers improvement in the PAPR compared to

normal OFDM system. However the PAPR improvement in modes of model (1) is

better than model (2) because of AMCl defines CR in model (1) based on SNR,

whereas CR in model (2) is defined based on target SER. The dependence of

definition the CR on SER restricts using low CR in the tested modes of model (2),

whereas the updating mechanism of CR in modes of model (1) has more freedom to

select low, moderate, or high CRs of each modulation scheme depends on SNR. To

summarize the overall results, the proposed AMCl algorithm in models (1) and (2)

shows its ability to provide OFDM system with high data rate transmission at all

SNRs.

The improvement in PAPR is clearly noticed in all tested systems. Despite

these models uses clipping technique, they can offer comparable SER performance

compared to the normal OFDM system. The results prove suitability of AMCl

algorithm in two models to all verified OFDM systems in terms of SER, PAPR, and

data throughput. For more accurate explanation the tested modes in model (1) are

more suitable to OFDM system that needs better improvement in PAPR and huge data

throughput at all SNRs with reasonable SER performance at low SNRs such as DVB-

T and 4G systems. However OFDM system that needs better and stable SER

performance with reasonable reduction in PAPR and high data throughput at all SNRs

such as IEEE 802.11g and IEEE 802.16e, the tested modes in model (2) can be the

best choice.

225

6.5 FUTURE WORK

This thesis focuses only on the effects of joint performance of the modulation

adaptation and the PAPR clipping technique. It is essential in any upcoming work to

analyze the joint performance of rate adaptation and power adaptation with PAPR

reduction mechanisms in OFDM systems. The analysis should cover three possible

cases, the first case when the transmit power is constant with only rate adaptation, the

second one when the rate is constant with only power adaptation, and the last case

with both power and rate adaptation. It is recommended to obtain the cumulative

distribution numerically of the PAPR in each of the above cases. Moreover, it is

important to find an optimization for the algorithm of the link adaptation mechanism.

The envelope of OFDM signal has large fluctuation in the time domain. This

fluctuation becomes more worse when OFDM system utilizes high order modulation

schemes such as 64-QAM, 128-QAM, and 256-QAM. The current expression of

PAPR meets OFDM that utilize low order modulation schemes such as 4-QAM, and

16-QAM. Long observation in this thesis shows that the amplitude of peaks in

OFDM-256QAM signal is larger than other schemes. Moreover the measured value of

PAPR is larger than theoretical value. This leads to necessity of developing the

analytical expression of the PAPR.

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APPENDICES

APPENDIX A

LIST OF PUBLICATIONS

JOURNALS

Ibrahim Ismail Al-kebsi, Mahamod Ismail, and Kasmiran Jumari. 2008. The Impact of Modulation Adaptation on PAPR Clipping Technique in OFDM of 4G System. Asian Network for Scientific Information Science (JAS). 8(15): 2776-2780.

(ANSI), Journal of Applied

Ibrahim Ismail Al-kebsi, Mahamod Ismail, Kasmiran Jumari, and T. A. Rahman. 2009. Mobile WiMAX Performance Improvement Using a Novel Algorithm with New Form of Adaptive Modulation. International Journal of Computer Science and Network Security

Ibrahim Ismail Al-kebsi, Mahamod Ismail, Kasmiran Jumari, and T. A. Rahman. 2009. Throughput Enhancement and Performance Improvement of the OFDM Based WLAN System.

(IJCSNS). 9(2):76-82.

International Journal of Computer Science and Network Security

Ibrahim Ismail Al-kebsi, Mahamod Ismail, Kasmiran Jumari, and T. A. Rahman. 2009. Eliminate the Effects of Clipping Technique on the SER performance by Recovering the Clipped Part of the OFDM Signal.

(IJCSNS). 9(4):138-148.

International Journal of Computer Science and Network Security

(IJCSNS). 9(7):37-45.

PROCEEDINGS

Ibrahim Ismail Al-kebsi, Mahamod Ismail and Kasmiran Jumari. 2008. The Impact of Adaptive Modulation and Power Control on Peak to Average Power Ratio in OFDM of 4G system. Proc. IEEE of 6th National Conference on Telecommunication Technologies and 2nd Malaysia Conference on Photonics(NCTT-MCP). PutraJaya, Malaysia. 2: 295-299.

Ibrahim Ismail Al-kebsi, Mahamod Ismail. 2008. The Impact of Link Adaptation and Power Control on PAPR Clipping Technique in OFDM system. Proc. of Engineering Postgraduate Conference (EPC). Kajang, Malaysia. 1:17-21.

234

Tharek A. Rahman, Mahamod Ismail, and Ibrahim Ismail Al-kebsi. 2008. The Impact of PAPR and ICI on the Performance of the Mobile WiMAX OFDMA System. Proc. of Malaysian Communications and Multimedia Commission (MCMC) colloquium. 18-19 ISBN: 978-983-42563-2-6.

Ibrahim Ismail Al-kebsi, Mahamod Ismail, Kasmiran Jumari, T. A. Rahman, and Ayman A. El-Saleh. 2009. A Novel Algorithm with a New Adaptive Modulation Form to Improve the Performance of OFDM for 4G Systems. Proc. IEEE of the International Conference on Future Computer and Communication (ICFCC), Kuala Lumpur, Malaysia. 1: 11-16.

Ayman A. El-Saleh, Mahamod Ismail, Mohd Alauddin Mohd Ali, and Ibrahim Ismail Al-kebsi. 2009. Capacity Optimization for Local and Cooperative Spectrum Sensing in Cognitive Radio Networks. Proc. IEEE of the International Conference on Future Computer and Communication (ICFCC). Kuala- Lumpur, Malaysia. 1:145-150.