用matlab仿真实现ldpc编解码，BPSK调制, 测定误码率与信噪比的关系

function [c, newH] = makeParityChk(dSource, H, strategy) % Generate parity check vector bases on LDPC matrix H using sparse LU decomposition % % dSource : Binary source (0/1) % H : LDPC matrix % strategy: Strategy for finding the next non-zero diagonal elements % {0} First : First non-zero found by column search % {1} Mincol : Minimum number of non-zeros in later columns % {2} Minprod: Minimum product of: % - Number of non-zeros its column minus 1 % - Number of non-zeros its row minus 1 % % c : Check bits % %---------------------------------------------% % % % 工作室提供代做matlab仿真 % % % % 详情请访问：http://cn.mikecrm.com/5k6v1DP % % % %---------------------------------------------% % Get the matric dimension [M, N] = size(H); % Set a new matrix F for LU decomposition F = H; % LU matrices L = zeros(M, N - M); U = zeros(M, N - M); % Re-order the M x (N - M) submatrix for i = 1:M % strategy {0 = First; 1 = Mincol; 2 = Minprod} switch strategy % Create diagonally structured matrix using 'First' strategy case {0} % Find non-zero elements (1s) for the diagonal [r, c] = find(F(:, i:end)); % Find non-zero diagonal element candidates rowIndex = find(r == i); % Find the first non-zero column chosenCol = c(rowIndex(1)) + (i - 1); % Create diagonally structured matrix using 'Mincol' strategy case {1} % Find non-zero elements (1s) for the diagonal [r, c] = find(F(:, i:end)); colWeight = sum(F(:, i:end), 1); % Find non-zero diagonal element candidates rowIndex = find(r == i); % Find the minimum column weight [x, ix] = min(colWeight(c(rowIndex))); % Add offset to the chosen row index to match the dimension of the... % original matrix F chosenCol = c(rowIndex(ix)) + (i - 1); % Create diagonally structured matrix using 'Minprod' strategy case {2} % Find non-zero elements (1s) for the diagonal [r, c] = find(F(:, i:end)); colWeight = sum(F(:, i:end), 1) - 1; rowWeight = sum(F(i, :), 2) - 1; % Find non-zero diagonal element candidates rowIndex = find(r == i); % Find the minimum product [x, ix] = min(colWeight(c(rowIndex))*rowWeight); % Add offset to the chosen row index to match the dimension of the... % original matrix F chosenCol = c(rowIndex(ix)) + (i - 1); otherwise fprintf('Please select columns re-ordering strategy!\n'); end % switch % Re-ordering columns of both H and F tmp1 = F(:, i); tmp2 = H(:, i); F(:, i) = F(:, chosenCol); H(:, i) = H(:, chosenCol); F(:, chosenCol) = tmp1; H(:, chosenCol) = tmp2; % Fill the LU matrices column by column L(i:end, i) = F(i:end, i); U(1:i, i) = F(1:i, i); % There will be no rows operation at the last row if i < M % Find the later rows with non-zero elements in column i [r2, c2] = find(F((i + 1):end, i)); % Add current row to the later rows which have a 1 in column i F((i + r2), :) = mod(F((i + r2), :) + repmat(F(i, :), length(r2), 1), 2); end % if end % for i % Find B.dsource z = mod(H(:, (N - M) + 1:end)*dSource, 2); % Parity check vector found by solving sparse LU c = mod(U\(L\z), 2); % Return the rearrange H newH = H; fprintf('Message encoded.\n');