Progress Report on OWDM-Based Cognitive Radio System

NTU Confidential

Progress Report on OWDM-Based Progress Report on OWDM-Based Cognitive Radio SystemCognitive Radio System

Presenter: Kuan-Hung ChenAdviser: Tzi-Dar Chiueh

March 28, 2005

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OutlineOutline

• Why Cognitive Radios?• Motivation• Orthogonal Wavelet Division Multiplexing

(OWDM)• OWDM-Based Cognitive Radio System• Simulation Results• Conclusions

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• In the near future, it is expected that the demand for bandwidth will increase substantially due to– more and more sophisticated wireless applications,– explosive increase of wireless LAN availability, and– growing demands on ubiquitous wireless access to

Internet.

• Scarcity of spectral resources reminds us spectrum should be used more efficiently.

• Cognitive Radio draws lots of attention.– It is proposed to improve spectrum utilization.– It should be smart enough to find out free spectrum

it can use.

Why Cognitive Radios?Why Cognitive Radios?

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Inefficiency on Spectrum Inefficiency on Spectrum UtilizationUtilization

[1]

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• Cognitive radio OFDM• OFDM modulation has some disadvantages

when only fragmentary spectrum is available.

MotivationMotivation

Frequency

TIM

E

… …

[2]

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IEEE 802.22IEEE 802.22

• In Dec. 2002, FCC begins to consider allowing unlicensed operation in licensed band [3][4].– TV bands below 900 MHz and in 3650-3700 MHz band

• It seems that the technology is not ready to support unlicensed operation in TV broadcast spectrum [5].

• A new working group is created in Nov. 2004 for cognitive wireless regional area network (WRAN) standardization.– Provide fixed, point to multi-point air interface– Prevent harmful interference to the licensed services

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• OWDM modulation has been studied extensively for xDSL applications or wireless communications.

• Better sidelobes attenuation is achievable by OWDM.

• A cognitive radio system applies the OWDM is proposed.

• Target band: TV band, GSM band, etc.

OWDM and Cognitive RadioOWDM and Cognitive Radio

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Orthogonal Wavelet Division Orthogonal Wavelet Division MultiplexingMultiplexing

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• A wave is usually defined as an oscillating function of time, such as a sinusoid.

• A wavelet is a “small wave”, which has its energy concentrated in time.

Introduction on WaveletIntroduction on Wavelet

[6]

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• Wavelet based multichannel modulation scheme.

• Implemented via overlapped waveforms to preserve data rate.

• Guard interval does not make sense in OWDM.

Orthogonal Wavelet Division Orthogonal Wavelet Division MultiplexingMultiplexing

Symbol Duration: T

T

T

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• The energy of each subchannel is much more concentrated in mainlobe than that in OFDM case.

Subchannel Spectrum Subchannel Spectrum PropertyProperty

OFDM Subchannel Spectrum OWDM Subchannel Spectrum

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• Indoor low-mobility wireless communication system

• Target band: TV band, GSM band, etc.

OWDM-based Cognitive Radio OWDM-based Cognitive Radio SystemSystem

CR AP

CR MT

Control channel

Traffic channel

PU

PU

PU: Primary user

CR: Cognitive Radio

AP: Access point

MT: Mobile terminal

Spectrum

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• Advantages– Higher spectral containment– More robust to narrowband interference

• Drawbacks– Higher complexity– More complex equalization

• Challenges– Low-complexity architecture development

Advantages and DrawbacksAdvantages and Drawbacks

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System SpecificationSystem Specification

Modulation type2-ary PAM, 4-ary PAM, 8-ary PAM

Subchannel number 256

Subchannels in use < 244

Carrier frequency

TV band: 478+4*l MHz, l=0, 1, …GSM band: 902.5 MHz, 947.5 MHz

Sampling Frequency

TV band: 24*n MHz, n=1, 2GSM band: 25.6 MHz

Subchannel SpacingTV band: 93.75*n kHz, n=1, 2GSM band: 100 kHz

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• Short Preamble: CFO estimation• Long Preamble: Symbol timing estimation• Training Symbol: Channel estimation for FEQ

initialization

Packet FormatPacket Format

Short PreambleLong

PreambleData

128 128128 128128 128

Training Symbol

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• Exponentially-modulated synthesis/analysis bank (EMSB/EMAB) are used to realize the OWDM modulation/demodulation.

System ArchitectureSystem Architecture

Receiver

Symbol timing

estimation

FromADC

CFO estimation

EMAB Slicer

Bit stream

S/ P Symbol map

EMSBS/ P

Transmitter

Spectrum sensing

Preamble generator

FEQ

Channel assign

TxOutput

CFOde-rotator

NCO

Training pattern

extraction

Channel estimation

Channel gain update

Maximum ratio

combining

Pilot extraction

ResidualCFO

estimation

LPF

To FEC

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• Multipath Rayleigh fading, SCO, CFO, AWGN

Channel ModelChannel Model

Tx

Delay

Delay

Delay

Rayleigh Fading Gain

r2

rL

Path Loss r1

CFO

Rx

AWGN

SCO

SCO

SCO

Channel Model

Nπεj

e2

2τ

1τ

Lτ

1α

2α

Lα

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• The length N used for moving average is adjustable.

CFO EstimatorCFO Estimator

0 63 127

＊

0 63 127

D-

+

+Delay Correlator

0 N-1

D

-

+ +

Moving Average

N/2a a>bb

D

| ·| 2

01

D10 tan-1 >>7

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• Parameters– Carrier frequency: 2.4 GHz– Sampling frequency: 80 MHz– CFO: 40 ppm

• The CFO estimator is randomly enabled during the first 64 samples of the second symbol in the short preamble.

• Three cases are simulated.– Case 1: CFO estimation is done using 256+N-1 samples.– Case 2: CFO estimation is done using 288+N-1 samples.– Case 3: CFO estimation is done using 320+N-1 samples.

• 5 schemes are done for each case.• 10000 runs are simulated for each scheme.

Simulation SetupsSimulation Setups

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Simulation ResultsSimulation Results

0.00460.00820.01480.0266Moving Average ( length 128 )




0.00470.00830.01490.0267No moving average

20 dB15 dB10 dB5 dB

SNRSquared MSE (%)






20 dB15 dB10 dB5 dB

SNRSquared MSE (%)






20 dB15 dB10 dB5 dB

SNRSquared MSE (%)






20 dB15 dB10 dB5 dB

SNRSquared MSE (%)






20 dB15 dB10 dB5 dB

SNRSquared MSE (%)






20 dB15 dB10 dB5 dB

SNRSquared MSE (%)

Case I

Case II

Case III

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• Case I: Without moving average, SNR = 5dB

Histogram of Percentage CFO Histogram of Percentage CFO Estimation ErrorEstimation Error

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• 100 symbols are transmitted for each run• 300 runs are simulated for each SNR• 2dB degradation under low SNR

Bit Error RatesBit Error Rates

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ConclusionsConclusions

• An OWDM-based cognitive radio system is proposed to operate in the bands where only fragmentary spectrum is available.

• Lower interference to primary systems can be achieved by OWDM modulation.

• Moving average is useless to improve the accuracy of CFO estimation.

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ReferenceReference

[1] E. Tsui, “What are Adaptive, Cognitive Radios?” in BWRC Winter Retreat, Jan. 13, 2004.

http://bwrc.eecs.berkeley.edu/Presentations/Retreats/Winter_Retreat_2004/Tuesday%20AM/ACR%20E%20Tsui.ppt

[2] B. Fette, “SDR Technology Implementation for the Cognitive Radio,” in Workshop on Cognitive Radio Technologies, Washington, DC, May 19, 2003.

ftp://ftp.fcc.gov/pub/Bureaus/Engineering_Technology/Documents/cognitive_radio/fcc_cognitive_radio_fette_v8.ppt

[3] B. Lane, “Cognitive Radio Technologies in the Commercial Arena,” in Workshop on Cognitive Radio Technologies, Washington, DC, May 19, 2003. ftp://ftp.fcc.gov/pub/Bureaus/Engineering_Technology/Documents/cognitive_radio/lane_cognitive_radio_5-19-03.ppt

[4] FCC, ET Docket 02-328.[5] Joint reply comments of the association for maximum service television, I

nc., the national association of broadcasters, and the association of public television stations.http://gullfoss2.fcc.gov/prod/ecfs/retrieve.cgi?native_or_pdf=pdf&id_document=6514088793

[6] C. S. Burrus, R. A. Gopinath, and H. Guo, Introduction to Wavelets and Wavelet Transforms, Prentice-Hall, Inc., 1998.

Progress Report on OWDM-Based Cognitive Radio System

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