mlse equalizer

[gokce]

hi;
how can ? do mlse equalizer with viterbi algorithm for ofdm.

thanks for u advance

you can send 'yoldas...@hotmail.com'

[gokce]

"gokce " <924...@mathworks.com> wrote in message <lldkjc$36m$1...@newscl01ah.mathworks.com>...
> hi;
> how can I do mlse equalizer with viterbi algorithm for ofdm.

>
> thanks for u advance
>
> you can send 'yoldas...@hotmail.com'

this is viterbi algorithm but I don't know mlse equalizer with viterbi algorithm

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% All rights reserved by Krishna Pillai, http://www.dsplog.com
% The file may not be re-distributed without explicit authorization
% from Krishna Pillai.
% Checked for proper operation with Octave Version 3.0.0
% Author : Krishna Pillai
% Email : kri...@dsplog.com
% Version : 1.0
% Date : 14th December 2008
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Script for computing BER with Binary Convolutional Code
% and Viterbi decoding.
% Convolutional code of Rate-1/2, Generator polynomial - [7,5] octal
% Hard decision decoding is used.

clear
N = 10^6 ;% number of bits or symbols

Eb_N0_dB = [0:1:10]; % multiple Eb/N0 values
Ec_N0_dB = Eb_N0_dB - 10*log10(2);

ref = [0 0 ; 0 1; 1 0 ; 1 1 ];

ipLUT = [ 0 0 0 0;...
0 0 0 0;...
1 1 0 0;...
0 0 1 1 ];

for yy = 1:length(Eb_N0_dB)

% Transmitter
ip = rand(1,N)>0.5; % generating 0,1 with equal probability

% convolutional coding, rate - 1/2, generator polynomial - [7,5] octal
cip1 = mod(conv(double(ip),[1 1 1 ]),2);
cip2 = mod(conv(double(ip),[1 0 1 ]),2);
cip = [cip1;cip2];
cip = cip(:).';

s = 2*cip-1; % BPSK modulation 0 -> -1; 1 -> 0

n = 1/sqrt(2)*[randn(size(cip)) + j*randn(size(cip))]; % white gaussian noise, 0dB variance

% Noise addition
y = s + 10^(-Ec_N0_dB(yy)/20)*n; % additive white gaussian noise

% receiver - hard decision decoding
cipHat = real(y)>0;

% Viterbi decoding
pathMetric = zeros(4,1); % path metric
survivorPath_v = zeros(4,length(y)/2); % survivor path

for ii = 1:length(y)/2
r = cipHat(2*ii-1:2*ii); % taking 2 coded bits

% computing the Hamming distance between ip coded sequence with [00;01;10;11]
rv = kron(ones(4,1),r);
hammingDist = sum(xor(rv,ref),2);


if (ii == 1) || (ii == 2)

% branch metric and path metric for state 0
bm1 = pathMetric(1,1) + hammingDist(1);
pathMetric_n(1,1) = bm1;
survivorPath(1,1) = 1;

% branch metric and path metric for state 1
bm1 = pathMetric(3,1) + hammingDist(3);
pathMetric_n(2,1) = bm1;
survivorPath(2,1) = 3;


% branch metric and path metric for state 2
bm1 = pathMetric(1,1) + hammingDist(4);
pathMetric_n(3,1) = bm1;
survivorPath(3,1) = 1;

% branch metric and path metric for state 3
bm1 = pathMetric(3,1) + hammingDist(2);
pathMetric_n(4,1) = bm1;
survivorPath(4,1) = 3;

else
% branch metric and path metric for state 0
bm1 = pathMetric(1,1) + hammingDist(1);
bm2 = pathMetric(2,1) + hammingDist(4);
[pathMetric_n(1,1) idx] = min([bm1,bm2]);
survivorPath(1,1) = idx;

% branch metric and path metric for state 1
bm1 = pathMetric(3,1) + hammingDist(3);
bm2 = pathMetric(4,1) + hammingDist(2);
[pathMetric_n(2,1) idx] = min([bm1,bm2]);
survivorPath(2,1) = idx+2;

% branch metric and path metric for state 2
bm1 = pathMetric(1,1) + hammingDist(4);
bm2 = pathMetric(2,1) + hammingDist(1);
[pathMetric_n(3,1) idx] = min([bm1,bm2]);
survivorPath(3,1) = idx;

% branch metric and path metric for state 3
bm1 = pathMetric(3,1) + hammingDist(2);
bm2 = pathMetric(4,1) + hammingDist(3);
[pathMetric_n(4,1) idx] = min([bm1,bm2]);
survivorPath(4,1) = idx+2;

end

pathMetric = pathMetric_n;
survivorPath_v(:,ii) = survivorPath;

end

% trace back unit
currState = 1;
ipHat_v = zeros(1,length(y)/2);
for jj = length(y)/2:-1:1
prevState = survivorPath_v(currState,jj);
ipHat_v(jj) = ipLUT(currState,prevState);
currState = prevState;
end

% counting the errors
nErrViterbi(yy) = size(find([ip- ipHat_v(1:N)]),2);

end

simBer_Viterbi = nErrViterbi/N; % simulated ber - Viterbi decoding BER

theoryBer = 0.5*erfc(sqrt(10.^(Eb_N0_dB/10))); % theoretical ber uncoded AWGN

close all
figure
semilogy(Eb_N0_dB,theoryBer,'bd-','LineWidth',2);
hold on
semilogy(Eb_N0_dB,simBer_Viterbi,'mp-','LineWidth',2);
axis([0 10 10^-5 0.5])
grid on
legend('theory - uncoded', 'simulation - Viterbi (rate-1/2, [7,5]_8)');
xlabel('Eb/No, dB');
ylabel('Bit Error Rate');
title('BER for BCC with Viterbi decoding for BPSK in AWGN');