LDPC码_和积算法_码长可以任意_输出多项式即可_译码输出软信息_matlab

function [uhat,iteration]=SPA_log(Lc,Hrow,Hcol,H,max_Iter,thresh) %% 参考 袁东风 p64 或王育民 p292 %associate this structure with all non zero elements of H % Rate = 0.5; % sigma2 = 1/(10^(SNR/10))/(2*Rate); % sigma^2 方差 [rows,cols]=size(H); %Prior Probabilities %先验概率 % Lc= 2*r/sigma^2; % Lc= zeros(1,length(r)); %initialization %初始化：对特定的信道预设信息比特的先验概率。 total_one=length(Hrow);% H中1的个数 Lq = sparse(Hrow,Hcol,0); Lr = sparse(Hrow,Hcol,0); for n=1:total_one Lq(Hrow(n),Hcol(n)) = Lc(Hcol(n)); end %迭代次数100 for iteration=1:max_Iter %horizontal step %横向步骤：由信息节点的先验概率按置信传播算法得出各校验节点的后验概率。 for i=1:rows colind=find(Lq(i,:)~=0); % colnum = length(colind); temp = -tanh(0.5*(Lq(i,colind))); Horizon_sum = prod(temp); T1 = Horizon_sum./temp; temp2 = log((1-T1)./(1+T1)); temp2(find(temp2>thresh))=thresh; temp2(find(temp2<-thresh))=-thresh; Lr(i,colind)=temp2; end %vertical step %纵向步骤：由校验节点的后验概率推算出信息节点的后验概率。 for j=1:cols rowind=find(Lr(:,j)~=0); rownum=length(rowind); LQ =sum(Lr(rowind,j))+Lc(j); if(LQ>0) x_est(j)=1; else x_est(j)=0; end for i=1:rownum Lq(rowind(i),j)= LQ-Lr(rowind(i),j); end end %如果判决条件满足，译码结束，否则继续迭代 err_test = sum(rem(x_est*H',2)); tempp = sum(x_est); if(err_test==0) break; end end uhat = x_est;