vit_dec.m

The Viterbi algorithm

function decod = vit_dec(u,constlen,codegen, puncpat) % 
% hardvit.m -- Hard decision decoding Viterbi algorithm.
% Default Rate = k/n without function
[next_state,output] = trellisgen(constlen,codegen);
WindowLen = 1; % tblen=10;
[in_len out_len] = size(codegen); % in_len=k,  out_len=n (without punc)
% Initialize the Viterbi algorithm.  dH.m is a function to compute the
% Hamming distance, which is the path metric that is minimized for
% hard decision decoding.

initvit2(next_state, output, WindowLen, 'dH'); % sqerr2 or dH
svec = [];     % Initialize state sequence through trellis to empty.
               % The output from the Viterbi algorithm will be svec.
%% DEPUNC (u to v)
k=0;i=0;
while (i<length(u))
    for j=1:length(puncpat)
        if (puncpat(j) == 0)
            k = k+1;
            v(k) = 0;
        else
            k = k+1;
            i = i+1;
            v(k) = u(i);
        end
    end
end
%%
% out_len = length(codegen);
T = length(v)/out_len;     % Number of message bits to send through channel
for t = 1:T
    first = out_len*t-(out_len-1);
    last = out_len*t;
    x=v(first:last);
    s = viterbi2(x);    % returns state estimate WindowLen in the past,
    if (s)              % or s is empty if not enough bits through channel.
        svec = [svec, s];
    end
end  % Loop t=1:T

% Flush remaining paths through trellis

svec = [svec, vitflush(0)];

% Translate estimate of states, svec, to estimates of message bits
% state-to-message bit conversion matrix:
wh=zeros(1,T); j = length(constlen);
for t=1:T
    for i=1:size(next_state,2)
        if (svec(t+1)-1==next_state(svec(t),i))
            ww = bitget(uint8(i-1), j:-1:1);
            first = in_len*t-(in_len-1);
            last = in_len*t;
            wh(first:last) = ww;
%             wh = [wh i-1];
        end
    end
end
% disp('decoder output by This program')
% disp(double(wh))
decod = double(wh);