BPSK系统仿真及误码率计算源程序

MATLAB程序：

主程序：

%Simulation of bpskAWGN

Max_SNR=10;

N_trials=1000;

N=200;

Eb=1;

ber_m=0;

for trial=1:1:N_trials

trial

msg=round(rand(1,N));

s=1-msg.*2;

n=randn(1,N)+j.*randn(1,N);

ber_v=[];

for snr_dB=1:2:Max_SNR

snr=10.^(snr_dB./10); N0=Eb./snr;

sgma=sqrt(N0./2);

y=sqrt(Eb).*s+sgma.*n; y1=sign(real(y));

y2=(1-y1)./2;

error=sum(abs( msg- y2)); ber_snr=error./N; %ber

ber_v=[ber_v,ber_snr];

end%for snr

ber_m=ber_m+ber_v;

end

ber=ber_m./N_trials; ber_theory=[];

for snr_db=1:2:Max_SNR

snr=10.^(snr_db./10);

snr_1=Qfunct(sqrt(2*snr));

ber_theory=[ber_theory,snr_1];

end

%绘图表示实际误码率与理论误码率

i=1:2:Max_SNR;

semilogy(i,ber,'-r',i,ber_theory,'*b');

xlabel('E_b/N_0 (dB)')

ylabel('BER')

legend('Monte Carlo', 'Theoretic')

子程序：

function y = Qfunct(x)

%QFUNC Q function.

% Y = QFUNC(X) returns 1 minus the cumulative distribution function of the

% standardized normal random variable for each element of X. X must be a real

% array. The Q function is defined as:

%

% Q(x) = 1/sqrt(2*pi) * integral from x to inf of exp(-t^2/2) dt

%

% It is related to the complementary error

function (erfc) according to

% Q(x) = 0.5 * erfc(x/sqrt(2))

if (~isreal(x) || ischar(x))

error('comm:qfunc:InvalidArg','The argument of the Q function must be a real array.');

end

y = 0.5 * erfc(x/sqrt(2));

return;