📄 map_decoder.asv
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function [likeli_ratio,extrin_information]=map_decoder(x,x1,CONS,prior_information)
% map algorithm,zero force RSC,in the first interation ,extrinc is zero sequence from decoder 1 to
% decoder 2
K=length(x);
for t=1:K
for l=1:8 % l is the trellis numbers
p_exp(k)=exp(prior_information(k));
p_1(k)=p_exp(k)/(1+p_exp(k));
p_0(k)=1/(1+p_exp(k));
[next_state_1,x_p]=nxt_stat1513(l-1,1);
R_r_1(t,next_state_1+1)=p_1(k)*exp(CONS*((x(t)-1)^2+(x1(t)-(2*x_p-1))^2));
[next_state_0,x_p]=nxt_stat1513(l-1,0);
R_r_0(t,next_state_0+1)=p_0(k)*exp(CONS*((x(t)+1)^2+(x1(t)-(2*x_p-1))^2));
end
end
A_a_initial(1)=1;
A_a_initial(2:8)=0;
for t=1:K
for ll=1:8
A_a(t,ll)=0;
end
A_a_totall(t)=0;
for ll=1:8
[next_state_0,x_p]=nxt_stat1513(ll-1,0);
[next_state_1,x_p]=nxt_stat1513(ll-1,1);
if t==1
A_a(t,next_state_0+1)=A_a(t,next_state_0+1)+A_a_initial(ll)*R_r_0(t,next_state_0+1);
A_a(t,next_state_1+1)=A_a(t,next_state_1+1)+A_a_initial(ll)*R_r_1(t,next_state_1+1);
else
A_a(t,next_state_0+1)=A_a(t,next_state_0+1)+A_a(t-1,ll)*R_r_0(t,next_state_0+1);
A_a(t,next_state_1+1)=A_a(t,next_state_1+1)+A_a(t-1,ll)*R_r_1(t,next_state_1+1);
end
end
for ll=1:8
A_a_totall(t)= A_a_totall(t)+A_a(t,ll);
end
for ll=1:8
A_a(t,ll)=A_a(t,ll)/A_a_totall(t);
end
end
B_b_K(1)=1;
B_b_K(2:8)=0;
for t=K-1:-1:1
for ll=1:8
B_b(t,ll)=0;
end
for ll=1:8
[next_state_0,x_p]=nxt_stat1513(ll-1,0);
[next_state_1,x_p]=nxt_stat1513(ll-1,1);
if t==K-1
B_b(t,ll)=B_b_K(next_state_0+1)*R_r_0(t+1,next_state_0+1)+B_b_K(next_state_1+1)*R_r_1(t+1,next_state_1+1);
else
B_b(t,ll)=B_b(t+1,next_state_0+1)*R_r_0(t+1,next_state_0+1)+B_b(t+1,next_state_1+1)*R_r_1(t+1,next_state_1+1);
end
end
for ll=1:8
end
end
for t=1:K
ln_1(t)=0;
ln_0(t)=0;
for ll=1:8
if t==1
[next_state_1,x_p]=nxt_stat1513(ll-1,1);
ln_1(t)=ln_1(t)+A_a_initial(ll)*R_r_1(t,next_state_1+1)*B_b(t,next_state_1+1);
[next_state_0,x_p]=nxt_stat1513(ll-1,0);
ln_0(t)=ln_0(t)+A_a_initial(ll)*R_r_0(t,next_state_0+1)*B_b(t,next_state_0+1);
else if t>1&t<K
[next_state_1,x_p]=nxt_stat1513(ll-1,1);
ln_1(t)=ln_1(t)+A_a(t-1,ll)*R_r_1(t,next_state_1+1)*B_b(t,next_state_1+1);
[next_state_0,x_p]=nxt_stat1513(ll-1,0);
ln_0(t)=ln_0(t)+A_a(t-1,ll)*R_r_0(t,next_state_0+1)*B_b(t,next_state_0+1);
else
[next_state_1,x_p]=nxt_stat1513(ll-1,1);
ln_1(t)=ln_1(t)+A_a(t-1,ll)*R_r_1(t,next_state_1+1)*B_b_K(next_state_1+1);
[next_state_0,x_p]=nxt_stat1513(ll-1,0);
ln_0(t)=ln_0(t)+A_a(t-1,ll)*R_r_0(t,next_state_0+1)*B_b_K(next_state_0+1);
end
end
ln_c(t)=log(ln_1(t)/ln_0(t));
if ln_c(t)>0
decision_c(t)=1;
else
decision_c(t)=0;
end
end
end
likeli_ratio=prior_information+ln_c;
extrin_information=ln_c+4*CONS*x;
% bit_error=0;
% for t=1:K
% if decision_c(t)~=C_information(t)
% bit_error=bit_error+1;
% end
% end
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