convolutional_trellis.m

20072010.rar:tubor,LDPC,convolution的部分代码

function trellis = convolutional_trellis(generator_matrix, system_info)

%
% This function accepts a polynomial description of the
% convolutional encoder and returns the corresponding trellis
% structure description. 

% Assumptions : a) Only 1 input bit, i.e. k = 1
%               b) Only binary states

memory_length = system_info.constraint_length - 1;
trellis.numStates = 2 ^ memory_length;

trellis.numInputSymbols = 2;
trellis.numOutputSymbols = 2 ^ system_info.n;
 
for state = 1:trellis.numStates    
    state_vector = de2bi(state - 1, memory_length, 'left-msb');
    for input_bit = 0:1
        trellis.nextStates(state,input_bit + 1) = bi2de([input_bit state_vector(1:(memory_length - 1))], 'left-msb');
        for output = 1:system_info.n
            binary_outputs(output) = rem(generator_matrix(output,:) * [input_bit state_vector]', 2);
        end
        trellis.nextOutputs(state,input_bit + 1) = bi2de(binary_outputs,'left-msb');
    end
end

counter = zeros(trellis.numStates);
for state = 1:trellis.numStates
    for bit = 1:2
        next_state = trellis.nextStates(state, bit) + 1;
        counter(next_state) = counter(next_state) + 1;
        trellis.lastStates(next_state, counter(next_state)) = state - 1;
        trellis.lastOutputs(next_state, counter(next_state)) = trellis.nextOutputs(state, bit);
        trellis.lastBits(next_state, counter(next_state)) = bit - 1;
    end
end