COVENTRY UNIVERSITY 1 COVENTRY UNIVERSITY FACULTY OF ENGINEERING & COMPUTING BACHELOR OF ENGINEERING (HONS) IN ELECTRICAL AND ELECTRONIC ENGINEERING A311SE Communications and networks COURSEWORK STUDENT NAME : M. Faazil Fairooz STUDENT ID NUMBER : 4701970 SUPERVISOR : DR. ROHAN MUNASINGHE
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COVENTRY UNIVERSITY
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COVENTRY UNIVERSITYFACULTY OF ENGINEERING & COMPUTING
BACHELOR OF ENGINEERING (HONS)IN
ELECTRICAL AND ELECTRONIC ENGINEERING
A311SE Communications and networks
COURSEWORK
STUDENT NAME : M. Faazil FairoozSTUDENT ID NUMBER : 4701970SUPERVISOR : DR. ROHAN MUNASINGHE
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TABLE OF CONTENTS:
Chapter 1: Abstract ………………..……………………………………………..…....…...……..51.1 Motivation……………………………...………………..…L………………………..........51.2 Methodologies and Result……………………………..…………….……..................…….51.3 Conclusion……………………………………………………..…………..…...................5
Chapter 3: QAM Background and Principal…………………………...................................…….7
3.1 Governing Principles3.2 Brief History of Evolution
3.3 Principle of Operations of Multilevel Digital Modulations
Chapter 4: Principle of Operations of M-Qam Modulation…………...… ……………………..11
4.1 Detail of Operations……………………………………………..…….……………..…114.2 Detail of Functionality……………………………………………...………………..…114.3Waveform Illustration for Better Understanding……………….……...………................11
Chapter 5: Parameters for Performance Measurement of M-Qam Modulation……....................13
Chapter 6: Design and Software Implementation………………….…….....................................14
6.1.1 Design Calculations………………………………………………………………...146.1.2 Calculate the number of bits per symbol k………………………………..……. 146.1.3 Phase calculation of wave design …………………………………….………….156.1.4 Prepare a table for binary bits to symbols assignment…………………………. 156.1.5 Draw the constellation diagram for given 8 M_QAM modulations…….…….....166.1.6 MATLAB program………………………………………………………….....…166.1.7 Final output Modulated wave……………………………………………............186.1.7 Screenshots ………………………………………………………………....…..19
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Chapter 7: Analysis/ conclusion on Results…………………………………………….……...20
The writer would like to send his distinct recognitions to his lecturers Dr. Rohan Munasingha and
Mr. Duminda for their great effort during the coursework and before.
Also, I would like to thank my parents for their standing behind me.
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CHAPTER 1: Abstract
1.1 Motivation
Over time, the globe is still improving and advancing around us, there is a lot essence and
personalities trying to change things around us in the field of communication but rather little
success is achieved in this technological stride, it’s the same in all humans they tend to live and
work with less effort and time and more efficiently and effectively
This project has been emotively dedicated to communication techniques, because we are in a fast growing
world, where it is called a global village for us to be in the streamline of that technology we have to have
very large and complex communication infrastructure is to be used where two main modulation schemes
has been used and tested in computer simulation environment for proper function.
which would be QAM (M-ary Quadrature Amplitude Modulation) and BPSK (Binary Phase Shift
Keying) modulation techniques the main objective of this project is to clearly understand and
hypothetically assess each problem given below, The first would be the understanding of QAM digital
modulation techniques and the second would be the design of a Hamming code and its error detection
mechanism.
1.2 Methodologies and Result
The methodology used firstly would be the calculating all mathematical numbers and variables
and then finally getting into matlab for computing and plotting purposes, where the accuracy of
mathematical calculated data could be tested. The second part of this report concentrates the
construction of the Hamming code using basic theory after this part has been accomplished, it
too will be fed into the computer for processing. For the above stated problem Matlab and
Simulink would be extensively used
1.3 Conclusion
Final results would that all mathematical parts would be solved and graphically represented. The
main outcome of this project would be that an in-depth knowledge is acquired when completing
this project
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CHAPTER 2: Introduction
2.1 Introduction
Telecommunications in recent times has greatly evolved, where new and newer technologies have
come in recent years. These technologies came in two forms mainly as analog and digital
communication. As a part of our project we mainly look into digital communications. Where QAM
techniques are used is large at hand. If it is to be seen in a nut shell QAM relates to the change in
the phase of the digital signal with relationship to the input signal.
2.2 Objective
The objective can be broken into a segment that would be
Goals
The goal of this project is to clearly understand the uses and purposes QAM and hamming code
to a BPSK modulated signal. And the clear idea of using matlab is also emphasized here.
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CHAPTER 3: QAM Background and Principal
3.1 Governing Principles
The fundamental definition of communication methodology is to transfer informative content from
any indicate any point, at whatever time and anyplace. In general, the communication framework
or communication channel is limited on this principle, but over the years this brainstorm is in
enduring enhancement. For instance, at the starting, individuals were utilizing blaze and drums as
indicators to transfer the qualified data, and this methodology just for little separation but now we
have enhanced communications frameworks now. Folks can talk and see one another from any
side or wherever on the earth, accurately, in the universe. Any communication framework,
basically built on these principals. Any QAM system, includes the following three parts shown as a
satellite communication diagram in Figure 3.1[refer block diagram for simplified version figure
3.2]
Figure 0-1: Satellite Communication Diagram (image courtesy to Wikipedia. org)
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d
Figure 0-2: block diagram Communication system
Whenever the data or info signal transmits over the carrier. It’s called modulating signal. Consider
for example a QAM sinusoidal carrier signal. The signal is modulated according to the input data
the modification is done on the carrier wave
The operation of adjusting the amplitude of carrier means that modulation of the amplitude of
carrier is called Amplitude Modulation. The data signal becomes modulating signal. Similarly
when a data or modulating signal adjusting the phase or the frequency of the carrier it is called
Angle Modulation, see Figure 3-3, below.
Figure 0-3: QAM waveform(image courtesy to Google image sourse)
Source (transmitter) Destination (receiver)Transmission Media
Noise
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3.2 Brief History of Evolution
M-ary Quadrature Amplitude Modulation more known as QAM was first introduced into the
market in the early 20th century.it was first designed as a method of transmitting complex digital
signals by the use of multilevel modulation. This technology was more concerned with signals
that were created out of more complex sources like speech or video encoding or data that was
more originated from computers and communication servers.
This method of modulation was more successful with signal encrypting and more so ever in
signal scrambling purposes. Where early military equipment’s like communication set and data
transmitters used this technology. This technology was taken further and hybrid adaptive
channel equalization was developed where the signal is set to deferent signal levels to reduce
and avoid long distance losses in communication sets. The source encoder may be used to
remove some of the redundancy which occurs in many sources such as speech, typically
reducing the transmission rate of the source.
3.3 Principle of Operations of Multilevel Digital Modulations
To first understand the operation of multilevel digital modulation we must first see why digital
modulation is used in the field of telecommunications and science
For all transmission to be possible there must be a possible transmission media where the signal
is generated (transmitter) and could travel for its intended destination were in communication we
call it as the receiver.
For all transmission media in communication there is only a static range of frequencies that is
available for transmission purpose, as this is available we could not possibly transmit in all
frequencies this could be disastrous, If a solution is not found and the data that we sent would not
be suitable for that channel. A successful scheme was found after extensive research is that to
alter a transmitting signal according to the information that is feed as input data, this alteration of
the signal is called as modulation. This data that is modulated could be received by the receiver
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and the data that is inside the signal could be recovered as the original data that was encoded this
is called as demodulation. See Figure 3-4, below
Figure 0-4: wave Spectrum (image courtesy to Wikipedia. org)
Text Definition Text DefinitionLF Low frequency SHF Super high frequency
MF Medium frequency EHF Extremely high frequencyHF High frequencyUHF Ultra high frequency
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CHAPTER 4: Principle of Operations of M-Qam Modulation
4.1 Detail of Operations
QAM is a modulation technique that is raised by the combination of PSK (Phase Shift Key) and
ASKS (Amplitude Shift Key) method. Therefore QAM has both the characteristics of PSK and
ASK in its carrier wave where the data is incorporated. However it is regarded as a PSK
waveform by specialist in the digital modulation world, But for the QAM modulator the carrier
wave is ASK modulated.
It is also possible and tested that two different signals could be transmitted on the same carrier
frequency by creating two identical copies of the same carrier frequency without harming or
cancellation of the original data signal that is to be transmitted; this is possible by the means of
shifting each wave by 90o QAM modulator block diagram See Figure 4-1, below
4.2 Detail of Functionality
For the functional scheme we could take that bit streams arrive at the serial to parallel converter
at time which is equal to T, then the bits are broken up and separated into two separate bit
streams where the data bits would enter D1 and D2 separately
Figure 5-1: wave Spectrum
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The data in the upper stream is then ASK modulated on the carrier frequency by multiplying the
bit streams with the carrier
QAM Modulation equation ( ) = ( ) cos 2 + ( ) sin 2 In QAM modulation we can observer a special characteristic where if the numbers of
states are increased we could have a higher data rate for a given bandwidth
But at a certain number of states there will be higher possible error rate which would be
due to noise and attenuation
4.3 Waveform Illustration for Better Understanding
Figure 5-1: Provides Final transmission wave and combined wave cycles
Here two analog QAM carrier waves are generated each 90 degrees out of phase with each other.These two waves are further combined and transmitted.
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CHAPTER 5: Parameters for Performance Measurement of M-Qam
M Modulation
Average Signal-to-Noise Ratio
Outage Probability Average Symbol Error Probability Noise power spectral density (W/Hz
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CHAPTER 6: Design and Software Implementation
6.1.1 Design Calculations
Circuit design for an 8 QAM modulator has been given below. See Figure 5-1,
Figure 6-1, Cct design has been given above for an 8 QAM system
Figure 4-2.(a) block diagram
Figure 4-2.(b) truth table = 86.1.2 Calculate the number of bits per symbol k
Therefore with value ‘M’ given we could calculate number of symbols. This would be K
= log ( )= log ( 8)= 3
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6.1.3 Phase calculation of wave design
6.1.4 Prepare a table for binary bits to symbols assignment. See Table 5-1, below
Bit Assignment Output
A B C Amplitude Phase
0 0 0 0.765 -135
0 0 1 1.848 -135
0 1 0 0.765 -45
0 1 1 1.848 -45
1 0 0 0.765 135
1 0 1 1.848 135
1 1 0 0.765 45
1 1 1 1.848 45
Table 5.1-Bit Assignment chart
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6.1.5 Draw the constellation diagram for given 8 M_QAM modulations.
See Figure 5-2, below
Figure 6-2, Constellation Diagram,
6.1.6 Write a MATLAB program to simulate the designed M_QAM digitalmodulation in your simulation result, show the output modulated signal together withrelated input binary signal
Wave that would be used is a digital signal with an input combination of[000001010011100101110111] See Figure 5-3, below
Figure 6-3: Input digital signal
Matlab coding is stated below
format long;clcclear allM=8;
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data='000001010011100101110111';A1=2; A2=4;f=2;t=linspace(0,1,900);time=[];Digital_signal=[];QAM_signal=[];N=length(data)/log2(M);phase=[0 0 pi/2 pi/2 pi pi (3*pi)/2 (3*pi)/2];phase_data=[];for k=1:3:length(data)
enddisp(['Position of error in codeword=',num2str(index)]);correctedcode = recd;correctedcode(index) = mod(recd(index)+1,2)%Corrected codeword%Strip off parity bitsmsg_decoded=correctedcode;msg_decoded=msg_decoded(1:4)
10.8.2 Simulation for comparison of Bit Error Rate (BER) for coded and uncoded
signals
% Script for computing BER with Hamming (7,4) code and maximal% likelihood hard decision decoding
% Noise additiony = s + 10^(-Ec_N0_dB(yy)/20)*n; % additive white gaussian noise
% ReceivercipHard = real(y)>0; % hard decision
% Hamming decodercipHardM = reshape(cipHard,7,N/4).';syndrome = mod(cipHardM*ht,2); % find the syndromesyndromeDec = sum(syndrome.*kron(ones(N/4,1),[4 2 1]),2); % converting the three bit syndrom to
decimalsyndromeDec(find(syndromeDec==0)) = 1; % to prevent simulation crash, assigning no error bits to
paritybitCorrIdx = bitIdx(syndromeDec); % find the bits to correctbitCorrIdx = bitCorrIdx + [0:N/4-1].'*7; % finding the index in the arraycipHard(bitCorrIdx) = ~cipHard(bitCorrIdx); % correcting bitsidx = kron(ones(1,N/4),[1:4]) + kron([0:N/4-1]*7,ones(1,4)); % index of data bitsipHat = cipHard(idx); % selecting data bits
% counting the errorsnErr(yy) = size(find([ip- ipHat]),2);
end
theoryBer = 0.5*erfc(sqrt(10.^(Eb_N0_dB/10))); % theoretical ber uncoded AWGNsimBer = nErr/N;