Chapter 4

Communication System Design

and Parameters

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CHAPTER 4 COMMUNICATION SYSTEM DESIGN

AND PARAMETERS

4.1. Introduction

In this chapter the design parameters and analysis factors are described which

were used while designing of proposed error control code for communication

system. Performance measure parameters and communication channel

parameters are presented. SNR and its variants and relationship among them

are derived. AWGN channel parameters and default values of these are

presented and at last of this chapter signal power consumption estimation are

given.

4.2. Communication System Design Components

Every communication system consist a transmitter and receiver joined via

several communication entities like source encoder, channel encoder,

modulator etc. These entities have been described in chapter 1. The channel

encoder is used to append the parity bits and channel decoder find out errors in

received block. Communication channel is exposed to noise sources which can

alter the bits or signals transmitted through this channel. For avoiding from

exposing to noise; signals are sent at high power in compare with noise

signals. In the proposed communication system error correction codes are used

so that signals can be sent at low power. The use of error correction code

avoids the data damage and loss.

This thesis is focus on error correction code so in this thesis mainly work done

on designing of error correction code. In chapter 5 the detailed designing of

encoder and decoder for block codes are given. In chapter 6 designing of

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convolutional encoder and decoder are given and BER performances of both

codes were calculated.

Figure 4.1 Components and Steps in Communication System

Error Control Coding

Error-control coding is a mechanism in which redundancies bits are added into

data to be transmitted so that receiver can detect or correct some of the errors.

These are two types:

Block code:

In this code the information/message bits and error control bits are in separate

blocks. Before encoding decoding process first data are compiled into blocks.

The message bits are divided into k size blocks and then encoding is

performed.

Convolutional code:

Convolutional codes are alternatives to block coding in which encoding and

decoding can take place on a continuous data bit stream instead of static block

Information Source

Error Control Coding

Modulation

Noisy Communication

Channel

Demodulation Error Control

Decoding Information

Receiver

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as was in block codes. A continuous bit stream is converted into a single

codeword which is also a bit stream.

4.3. Communication System Analysis Parameters

There are some considerations which have to be taken while designing the

communication system. The system has many parameters and factors which

affect the performance of communication system. In this section related to

error control code and communication system; some important design

considerations and analysis factors are described.

1. Redundancy: The inclusion of extra error controlling bits which are

necessary to append with the message bits for detection and correction the

errors. These bits are calculated by predefined mathematical rules known as

encoding process. More redundancy bits have more error correction

capabilities if an optimized encoding algorithm is used. High redundancy

requires high bandwidth so while designing an error correction code it was

focused that with low redundancy; maximum number of errors must be

corrected.

2. BER: In digital communication BER is defined as the ratio of number of bit

errors to the total number of transferred bits during a studied time interval.

During the transmission, number of bits in communication channel has been

altered due to noise, interference, distortion or bit synchronization errors.

While designing a communication system or error control code it was focused

that BER must be minimized.

3. Extensibility: The communication system or error control code can be

expanded, and improved when required and error correction capabilities could

be increased.

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4. Modularity: The communication system consists of individual blocks in its

construction and every module or entity treats the incoming bits or signals

from one module to the other as an output source.

5. Usability: The error control code widely designed for space and satellite

communication but it can be in mobile communication systems and in other

communication networks.

4.3.1. Performance Analysis Factors

To evaluate the performance of error correcting code, several performance

measure metrics such as error correction capability, encoding decoding delay

and error controlling bit overhead are commonly used. The analysis of error

correcting codes can be done on the basis of hardware and software

performance of the codes.

4.3.2. Hardware Parameters

This analysis is performed on hardware or simulator. For hardware

performance of the code following parameters can be considered:

1. Probability of Uncorrected Errors.

2. Signal Power Consumption

3. Encoding/ Decoding Delay

4. Encoder/ Decoder Hardware Complexity

5. Number of Hardware Components

The error correcting codes can be analyzed on the basis of overhead (in terms

of redundant bits) and error correction capabilities of codes. The term

overhead is used to describe the redundant bits. More overhead requires more

bandwidth. For example, maintaining an audit trail might result in 10%

overhead, meaning that the program will run 10% slower when the audit trail

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is turned on. Programmers often need to weigh the overhead of new features

before implementing them.

4.3.3. Software Parameters

When to design hardware encoder is very complex and costly then software

based encoding decoding is used. This uses some encoding decoding

algorithm and calculates the parity bits (overhead). A good error correction

method has low overhead and better error correction capabilities. The

performance analysis of error correcting codes can be performed on the basis

of software parameters. The analysis parameters are:-

1. Overhead (Error Control Bits)

2. Encoding/Decoding delay

3. Bit Error Ratio (BER)

4. Energy/bit(Eb) and EbN0

4.4. Transmit Power and Error Control Coding

Concept of transmit power is used with respect to distance, less distance

requires less transmit power while large distance requires greater transmit

power. Similarly, Error Control Codes are used for efficient data transmission,

Block Codes or Convolutional Codes are types of them.

Signal transmitted with minimum power is an efficient source of energy

minimization. Receiver has to maintain a minimum signal to noise power

called EbN0 for successful operation. Transmit power required to transmit a

signal represented by Ptx in free space model is given by (1).

…..(1)

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..…(2)

Here, Eb is minimum energy that is required for one bit where N0 is noise

power spectral density, is spectral efficiency expressed as information rate to

bandwidth ratio, m noise proportionality constant, K Boltzman constant and T

absolute temperature all together represents signal noise represents

transmitted wavelength at some distance represented by d in free space model.

Transmitted power of signal depends on distance between transmitter and

receiver. If it is short then less transmit power is required and if it's large then

signal has to be transmitted with maximum power. When distance is greater

than sometimes data needs to be retransmitted by using some FEC code. So

that actual data should be sent and received with in time.

Additional parity bits are appended with information bits for receiving exact

information that was originally transmitted. For example, information or

message that is being sent is m of length k and extra parity bits are r added to

information bits m to form a codeword c, these extra redundant bits enables

decoder to correctly decode c. When data is sent through a noisy channel

where error occurring chances are high then error correction code minimize

the errors and low BER may be obtained at lower SNR value. Difference

between SNR levels to reach a certain BER value in coded and un-coded

system is called coding gain.

Required transmit power is divided by transmission rate which is equal to

energy required per bit. For calculating this power consumed by data or total

information bits which are being transmitted is divided by total bits. Energy

per bit required for transmitting data by un-coded system and that for coded

system is calculated from given formulas. Where coded data transmission

requires code gain values for energy calculation.

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.…..(3.1)

……(3.2)

Eq. (3.3) below gives energy saving from either coded or un-coded data

transmission

……(3.3)

Signal to Noise Ratio (SNR)

In the previous chapters model of communication system already has been

studied and the aim of this thesis is to minimize signal power consumption by

using error control coding. The performance of different error control coding

schemes in the presence of noise will be measured in terms of the signal-to-

noise ratio (SNR) at the output of the receiver, defined as

SNR = average power of message signal at the receiver output/average power

of noise at the receiver output.

Eb/N0 is another important parameter in digital communication which

normalizes SNR into SNR per bit. This parameter is used in performance

measurement of error control code in terms of BER. It is a ratio of energy per

bit to noise power spectral density, where Eb is the signal energy associated

with each user data bit. It is calculated by signal power divided by user bit

rate, unit of it is joules if signal power in watts and bit rate in bits/second. N0

is the noise spectral density, measured in watts per hertz or joules.

The channel distorts the signal, and noise accumulates along the path. Worse

yet, the signal strength decreases while the noise level increases with distance

from the transmitter. Thus the SNR is continuously decreasing along the

length of the channel. Amplifiers will increase both the signal and the noise,

and may indeed introduce more noise of their own.

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4.5. Signal Power Consumption Estimation

While designing of most digital communications systems one or more these

factors are considered: bandwidth efficient, power efficient, or cost efficient.

Power efficiency describes the ability of the system to reliably send

information at the lowest practical power level.

For calculating power consumption Matlab simulation was used. Messages

were transmitted without error control code and with error control code. On

the same BER the signal power was measured that is the power gain obtained

by error control code.

The signals were transmitted through AWGN channel and then white

Gaussian noise was added. Without using error control code some value of

Eb/N0 was set and after using error control code lower value of Eb/N0 was set

and then power gain was calculated. In the AWGN channel some parameters

were set manually and remaining was taken by default values.

4.5.1. Signal Power and Power Gain

A signal is a single-valued function of time that conveys information from

source to receiver and at every point in time has a unique value and this value

may either be a real number, or a complex number. It may be analog or digital,

an analog signal is a continuous function of time, for which the amplitude is

also continuous and it arises whenever a physical waveform is converted to an

electrical signal. A digital signal is a discrete function of time, for which the

amplitude can only have a finite set of values. Sometimes a distinction is also

made of discrete-time signals—these are signals that are a discrete function of

time, but the amplitude may take on a continuum of values. The instantaneous

power of a voltage or current signal is given by P = |v(t)|2 / R or P = |i(t)|

2 R,

where R is the resistance.

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Signal Power Gain is defined as the reduction in Es/N0 permissible for a coded

communication system to obtain the same probability of error as an un-coded

system.

4.5.2. Relationship between SNR and EbN0

The relationship between Eb/N0 and SNR have several forums, whether SNR

and Eb/N0 are same or not, the relationship is very easier to understand.

Let’s start with the basic equation and try to verify its authenticity.

S/Rb = Eb → (1)

where,

Rb = bit rate in bits/second

Eb = Energy per bit in Joules/bit

S = Total Signal power in Watts

As it is known from fundamental physics that Power = Energy/Time. Using SI

units, let’s verify the above equation.

S/Rb = Eb

Wattsbitssecond = JoulesbitWattsbitssecond = Joulesbit

⇒Watts = Joulessecond

This verifies the power, energy relationship between Ss and Eb. Now,

introducing the noise power N0 in equation (1)

⇒EbN0 = S(Rb∗N0)

⇒SNR = (Rb∗Eb)/N0 → (2)

This equation implies that the SNR will be more than EbN0 by a factor

of Rb (if Rb > 1 bit/second).

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Increasing the data rate will increase the SNR, however, increasing Rb will

also cause more noise and noise term also increases (due to ISI – intersymbol

interference, since more bits are packed closer and sent through the channel).

So SNR cannot be increased by simply increasing Rb. This must strike a

compromise between the data rate and the amount of noise that a receiver can

handle.

4.6. AWGN Channel Parameters

In practice, the digital signal is still transmitted by analogue waveforms.

Although the noise applied to the transmission waveforms takes many forms,

they are all analogue in manner one way or the other. Additive White

Gaussian Noise (AWGN) channel model is a basic noise model which is

generally accepted model for communication. It adds white noise with a

constant spectral density (expressed as watts per hertz of bandwidth) and a

Gaussian distribution of amplitude in transmitted signals.

The AWGN Channel adds real Gaussian noise and produces a real output

signal when input is complex signal then output also complex signal. In the

AWGN channel a variable number of parameters can be set. The parameter

names and its values are given and if not provided then default values are

taken automatically.

hChan = comm.AWGNChannel (Name1, Value1,..., NameN, ValueN); it

creates an AWGN channel object hChan with specified arguments. The

following parameters (arguments) can be specified and given values for an

AWGN channel.

NoiseMethod: - It is used for specifying noise level as one of Eb/No, Es/No,

SNR, and variance. The default argument is Eb/No.

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EbNo: - It is energy per bit to noise power spectral density ratio and it is unit

less entity that is given in decibels and its default value is 10.

EsNo: - It is energy per symbol to noise power spectral density ratio and it is

also unit less entity that is given in decibels and its default value is also10.

SNR: - It is signal to noise ratio which is a numeric or real value applies when

NoiseMethod properties is used. Its default value is 10.

BitsPerSymbol: - It is number of bits which are assigned to each input symbol

when noise method property is set to Eb/No and its default value is 1 bit.

SignalPower: - it specifies the mean square power of the input signal in Watts

and it is applied when noise method is used. The default value is 1 and

nominal impedance is 1 Ω.

SamplesPerSymbol: - It specifies the number of samples per symbol and its

default value is 1.

4.7. Results and Conclusion

In this chapter communication system design parameters and analysis factors

for error control code were described. Transmit power and its estimation in

EbN0 and EsN0 were derived. The relationship between SNR and its variants

were presented. The common parameters used in MATLAB for chapter 5 and

6 were presented and AWGN channel common parameters were set and its

default values were elaborated.