%Comparison of Decode and F,and Amplify and Forward
%BPSK in flat fading with Rayleigh:
%plot simulation results of BER and theoratical results for it using averaged BER
clc
clear all
close all
sum_dcf = 0;
sum_af = 0;
inputfilename = '9.wav';
[x, fs] =wavread(inputfilename);
%%%%%%%%%%%%%%%%%%%User1:Source%%%%%%%%%%%%%%
N_bits = length(x); %Number of data bits
%number of iterations over which the results are going to be averaged
N_iter = 15;
for iter = 1:N_iter
data = round(rand(N_bits,1));%random data bits
%channel coding using rate 1/2 convolutional code:
trellis = poly2trellis(3,[5 7]); %trellis structure
c_data = convenc(data,trellis);
%BPSK modulation
tx = 2*c_data - 1;
%%%%%%%%%Channel characteristics%%%%%%%%%%%%%%%%
SNRdB = -3:40; %Range of SNR for which BER is investigated.
%additive noise and channel response for the relay channel:
%Source uplink channel:
noise_d = 1/sqrt(2) * (randn(2 * N_bits,1) + j * randn(2 * N_bits,1));
h_d = 1/sqrt(2) * (randn(2 * N_bits,1) + j * randn(2 * N_bits,1));
%interuser channel:
noise_r1 = 1/sqrt(2) * (randn(2 * N_bits,1) + j * randn(2 * N_bits,1));
h_r1 = 1/sqrt(2) * (randn(2 * N_bits,1) + j * randn(2 * N_bits,1));
%for Relay uplink:
noise_r2 = 1/sqrt(2) * (randn(2 * N_bits,1) + j * randn(2 * N_bits,1));
h_r2 = 1/sqrt(2) * (randn(2 * N_bits,1) + j * randn(2 * N_bits,1));
for k = 1:length(SNRdB)
SNR = 10^(SNRdB(k)/10); %convert SNRdB to linear value SNR
ftx_r1 = sqrt(SNR) * h_r1 .* tx + noise_r1;
%%%%%%%%%%%%%%%%% At the Relay %%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%Decode & Forward %%%%%%
%equalizing at relay
eq_rx1 = ftx_r1 .* conj(h_r1);
%hard decision and converting from bipolar to bits
r_bits = (sign(real(eq_rx1)) + 1)/2;
%channel decoding:
dec_dcf_r1 = vitdec(r_bits,trellis,3,'term','hard');
%re-encoding using the same procedure as Source:
c_data2 = convenc(dec_dcf_r1,trellis);
%BPSK signal for the relay coded data:
tx2_dcf = 2 * c_data2 - 1;
%%%%%%%%%%%%%%%%%%%%Apmlify & Forward%%%%%%%%%%%%%%%%%%%
beta = sqrt(1./((SNR * abs(h_r1).^2) + 1));
%amplification:
ftx_amp = ftx_r1 .* beta;
%%%%%%%%%%%%%%%%%%%%%%%%%%Relay to Destination%
%DCF
ftx_dcf_r2 = sqrt(SNR) * tx2_dcf .* h_r2 + noise_r2 ;
%AF
ftx_af_r2 = sqrt(SNR) * ftx_amp .* h_r2 + noise_r2 ;
%%%%%%%%%%%%%%%%% At the Destination%%%%%%%%%%%
ftx_d = sqrt(SNR)* tx .* h_d + noise_d;
%%%%%%%%%%%%%%%%%%%%%%%%DCF%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%MRC%%%%%%%%%%%%%%%
R_dcf = ftx_dcf_r2 .* conj(h_r2) + ftx_d .* conj(h_d);
%hard decisioning
dec_com_dcf = sign(real(R_dcf));
%%%%%%%%%%%BER calculations%%%%%%%%%%%%%%%%%%
%at destination:
err_com1(k) = sum(abs(dec_com_dcf - tx)/2);
simber_com1(k) = err_com1(k) / (2 * N_bits);
%%%%%%%%%%%%%%%%%%%%%%%%AF%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%MRC%%%%%%%%%%%%%%%
R_af = ftx_af_r2 .* conj(h_r2) .* conj(h_r1) + ftx_d .* conj(h_d);
dec_com_af = sign(real(R_af));
%%%%%%%%%%%BER calculations%%%%%%%%%%%%%%%%%%%at destination:
err_com3(k) = sum(abs(dec_com_af - tx)/2);
simber_com3(k) = err_com3(k) / (2 * N_bits);
%theoratical rayleigh
theberrayleigh(k) = 0.5 * (1 - sqrt(SNR./(1 + SNR)));
mue = sqrt(SNR/(1+SNR));
mrcth(k) = 0.25 * (2 + mue) * (1-mue)^2;%theoratical 2Rx MRC
end
sum_dcf = sum_dcf + simber_com1;
sum_af = sum_af + simber_com3;
end
%average BER:
avgber_dcf = sum_dcf/N_iter;
avgber_af = sum_af/N_iter;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%BER plots%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
figure
semilogy(SNRdB,avgber_dcf,'--or',SNRdB,avgber_af,'--sg',SNRdB,theberrayleigh,'--xb',SNRdB,mrcth,'--pk');
axis([SNRdB(1) max(SNRdB) 10^-5 0.5]);
%grid on
legend('DCF','AF','Rayleigh','MRC');
xlabel('SNR dB');
ylabel('BER');
title(['BER curves for comparison,(averaged for ',num2str(N_iter),' iterations)']);
