matlab-基于差错检测的DF协作通信链路matlab仿真,包括8PSK,最大合并比接收,维特比译码-源码

function [decoder_output,survivor_state,cumulated_metric]=viterbi(channel_output) k=2; G=[0 0 1 0 1 0 0 1;0 0 0 0 0 0 0 1;1 0 0 0 0 0 0 1]; %k=1; %G=[0 1 0 1 1 1;1 0 0 0 1 1;0 1 1 0 0 1;1 0 0 1 0 1]; n=size(G,1); %检验G的维数 if rem(size(G,2),k)~=0 error('Size of G and k do not agree') end if rem(size(channel_output,2),n)~=0 error('channle output not of the right size') end L=size(G,2)/k; number_of_states=2^((L-1)*k); %产生状态转移矩阵，输出矩阵和输入矩阵 for j=0:number_of_states-1 for t=0:2^k-1 [next_state,memory_contents]=nxt_stat(j,t,L,k); input(j+1,next_state+1)=t; branch_output=rem(memory_contents*G',2); nextstate(j+1,t+1)=next_state; output(j+1,t+1)=bin2deci(branch_output); end end input; state_metric=zeros(number_of_states,2); depth_of_trellis=length(channel_output)/n; channel_output_matrix=reshape(channel_output,n,depth_of_trellis); survivor_state=zeros(number_of_states,depth_of_trellis+1); [row_survivor col_survivor]=size(survivor_state); %开始非尾信道输出的解码 %i为段，j为每一阶段的状态，t为输入 for i=1:depth_of_trellis-L+1 flag=zeros(1,number_of_states); if i<=L step=2^((L-i)*k); else step=1; end for j=0:step:number_of_states-1 for t=0:2^k-1 branch_metric=0; binary_output=deci2bin(output(j+1,t+1),n); for tt=1:n branch_metric=branch_metric+metric(channel_output_matrix(tt,i),binary_output(tt)); end if ((state_metric(nextstate(j+1,t+1)+1,2)>state_metric(j+1,1)+branch_metric)|flag(nextstate(j+1,t+1)+1)==0) state_metric(nextstate(j+1,t+1)+1,2)=state_metric(j+1,1)+branch_metric; survivor_state(nextstate(j+1,t+1)+1,i+1)=j; flag(nextstate(j+1,t+1)+1)=1; end end end state_metric=state_metric(:,2:-1:1); end %开始尾信道输出的解码 for i=depth_of_trellis-L+2:depth_of_trellis flag=zeros(1,number_of_states); last_stop=number_of_states/(2^((i-depth_of_trellis+L-2)*k)); for j=0:last_stop-1 branch_metric=0; binary_output=deci2bin(output(j+1,1),n); for tt=1:n branch_metric=branch_metric+metric(channel_output_matrix(tt,i),binary_output(tt)); end if ((state_metric(nextstate(j+1,1)+1,2)>state_metric(j+1,1)+branch_metric)|flag(nextstate(j+1,1)+1)==0) state_metric(nextstate(j+1,1)+1,2)=state_metric(j+1,1)+branch_metric; survivor_state(nextstate(j+1,1)+1,i+1)=j; flag(nextstate(j+1,1)+1)=1; end end state_metric=state_metric(:,2:-1:1); end %从最优路径产生解码输出 %由段得到状态序列，再由状序列从input矩阵中得到该段的输出 state_sequence=zeros(1,depth_of_trellis+1); size(state_sequence); state_sequence(1,depth_of_trellis)=survivor_state(1,depth_of_trellis+1); for i=1:depth_of_trellis state_sequence(1,depth_of_trellis-i+1)=survivor_state((state_sequence(1,depth_of_trellis+2-i)+1),depth_of_trellis-i+2); end state_sequence; decoder_output_matrix=zeros(k,depth_of_trellis-L+1); for i=1:depth_of_trellis-L+1 dec_output_deci=input(state_sequence(1,i)+1,state_sequence(1,i+1)+1); dec_output_bin=deci2bin(dec_output_deci,k); decoder_output_matrix(:,i)=dec_output_bin(k:-1:1)'; end decoder_output=reshape(decoder_output_matrix,1,k*(depth_of_trellis-L+1)); cumulated_metric=state_metric(1,1);