ME End Sem Programs

8/2/2019 ME End Sem Programs

1/8

Expt. No. 1

Date:

Single parity: Encoding and Decoding

Aim:

To write a MATLAB program to en code and decode single parity codes.

Apparatus required:

MATLAB 7 Software, Computer, Printer , Word processing software.

Basic Theory:

Program

Program 1: Generation of parity%this program will generate single parity bitclc;clear all;%Data to be encoded in even parityx=[1 0 1 0 1 1 0 1 1];disp('data to be encoded is')xy=length(x);z=zeros(1,y+1);%the following will be again data but with last bit as zeroz(1:y)=x;a=sum(x);if rem(a,2)==1z(y+1)=1;elsez(y+1)=0;enddisp('encoded data is')zProgram 2:Checkingofparity

%this program will check parityclc; clear all;x=[1 0 1 0 1 1 0 1 1];y=sum(x);if rem(y,2)==1disp('odd')elsedisp('even')end


2/8

Observation:

Program 1

data to be encoded is

x = 1 0 1 0 1 1 0 1 1

encoded data is

z = 1 0 1 0 1 1 0 1 1 0

Program 2:

even

Result:

A program to encode and decode using single parity code is demonstrated


3/8

Expt. No. 2

Date:

Hamming code: Encoding and Decoding

Aim:

To write a MATLAB program to en code and decode Hamming codes given the parity Matrix.

Apparatus required:


Basic Theory:

Data = [1 0 1 1]

Code = Data * G = [1 0 0 1 0 1 1]

Decode = code * HT

= [ 0 0 0] if no error in transmission

Program


4/8

% Encodingclc;% Parity matrix givenp=[1 1 0;0 1 1;1 1 1;1 0 1]% I matrix constructedi=[1 0 0 0;0 1 0 0;0 0 1 0;0 0 0 1]% G matrix constructedg=[p i]% Data to be encodedx=[1 1 0 1]% Multiplication with generation matrixfor j=1:7y=x*g(:,j);z=sum(y);s=rem(z,2);if s==1d(j)=0;elsed(j)=1;end

enddisp('the encoded message is')d

%decodingi1=eye(3,3)p1=p'h=[i1 p1]% H transposeh1 = h'% Multiplicationfor j1=1:3y1=d*h1(:,j1);

z1=sum(y1);s1=rem(z1,2);if s1==1d1(j1)=1;elsed1(j1)=0;endenddisp('the decoded message is')d1

Observation:

p =

1 1 0

0 1 1

1 1 1

1 0 1

i =


5/8

1 0 0 0

0 1 0 0

0 0 1 0

0 0 0 1

g =

1 1 0 1 0 0 0

0 1 1 0 1 0 0

1 1 1 0 0 1 0

1 0 1 0 0 0 1

x =

1 1 0 1

The encoded message is

d = 1 1 1 0 0 1 0

i1 = 1 0 0

0 1 0

0 0 1

p1 = 1 0 1 1

1 1 1 0

0 1 1 1

h = 1 0 0 1 0 1 1

0 1 0 1 1 1 0

0 0 1 0 1 1 1

h1 = 1 0 0

0 1 0

0 0 1

1 1 0

0 1 1

1 1 1

1 0 1

The decoded message is

d1 = 0 0 0

Result:

A program to encode and decode using Hamming code is demonstrated


6/8

Expt. No. 3

Date:

Equalization

Aim:

To write a MATLAB program to demonstrate Linear and MLSE equalizers

Apparatus required:


%This program is written by SPK.Babu for the M.E. Students.%This program demonstrates the equalization by Linear adaptive equalizer%using LMS algorithm and MLSE equalizer. The BER of the above is compared%with AWGN channel. The modulation used is BPSK%Since AWGN is used don't go for without equalization!!!!%DFE with RLS algorithm is yet to be developed in this program.clc; clear all; close all;% Set up parameters and signals.M = 2; % Alphabet size for modulationd = 1; d1 =1;for snr = 5:1:15msg = randint(100000,1,M); % Random messagemodmsg = pskmod(msg,M); % Modulate using QPSK.trainlen = 500; % Length of training sequencechan = [.986; .845; .237; .123+.31i];% Channel coefficients

filtmsg1 = filter(chan,1,modmsg); % Introduce channel distortion.filtmsg = awgn(filtmsg1, snr, 'measured');% Equalize the received signal.eq1 = lineareq(8, lms(0.01)); % Create an equalizer object.[symbolest,yd] = equalize(eq1,filtmsg,modmsg(1:trainlen));% Equalize.% Compute error rates with and without equalization.demodmsg = pskdemod(yd,M); % Demodulate detected signal from equalizer.[neq,req(d)] = biterr(demodmsg(trainlen+1:end),msg(trainlen+1:end));dd = d+1;endberlinear = req;const = pskmod([0:M-1],M)for SNR = 5:1:15%Generation of data bitsx = randint(1000000,1,M);

msg = pskmod(x,M); % Modulated messagechcoeffs = [.986; .845; .237; .12345+.31i];% Channel coefficientsfiltmsg1 = filter(chcoeffs,1,msg);% Introduce channel distortion.filtmsg = awgn(filtmsg1,SNR, 'measured'); % Introduce Noisetblen = 10; % Traceback depth for equalizerchanest = chcoeffs; % Assume the channel is known exactly (No channel

estimation performed).


7/8

msgEq = mlseeq(filtmsg,chanest,const,tblen,'rst'); % Equalize.msgeq1 = pskdemod(msgEq, M); % Demodulation into bits[a b(d1)]= biterr(x,msgeq1); % Calculate BER for each SNRd1d1 = d1+1;endbermlse = b;%---------Plotting the BER values----------semilogy(5:1:15, berlinear, 'r-o')hold onsemilogy(5:1:15, bermlse, 'g-*')bertheory = berawgn(5:1:15, 'psk', M, 'nondiff');semilogy(5:1:15, bertheory, 'b-^')axis([5 15 1E-6 1]); grid on;xlabel('SNR in dB'); ylabel('BER');legend('BER of Linear Equalizer', ' BER of MLSE Equalizer', 'BER of

theoritical BER under AWGN')

5 6 7 8 9 10 11 12 13 14 1510

-6

10-5

10-4

10

-3

10-2

10-1

100

SNR in dB

BER

BER of Linear Equalizer

BER of MLSE Equalizer

BER of theoritical BER under AWGN


8/8

Mini project titles

1. Simulate the Channel Model B: IEEE P802.11n Wireless LANs, "TGn Channel Models", IEEE802.11-03/940r4, 2004-05-10.

2. Simulation of Eye Diagram3. SC-FDMA physical layer SISO4. Simulink: FSK VS MSK Vs GMSK BER5. Simulink: BPSK Vs QPSK BER6. Simulate the following channel

7. Demonstrate any one of the error correcting coding performance on BER of QPSK with AWGNand Rayleigh channel.

8. Write a simple program to demonstrate precoding used along with equalizers to attain goodBER

Documents

ME End Sem Programs