0 and 1
if (temp<0.25), % with probability 1/4, source output is \
dsource1(i)=0; dsource2(i)=0;
elseif (temp<0.5), % with probability 1/4, source output is \
dsource1(i)=0; dsource2(i)=1;
elseif (temp<0.75), % with probability 1/4, source output is \
dsource1(i)=1; dsource2(i)=0;
else % with probability 1/4, source output is \
dsource1(i)=1; dsource2(i)=1; end; end;
% detection and the probability of error calculation
for i=1:N,
ray=raylrnd(0.8);
n=sgma*randn(1,2); % 2 normal distributed r.v with 0, variance sgma
if ((dsource1(i)==0) & (dsource2(i)==0)), r=ray*s00+n;
elseif ((dsource1(i)==0) & (dsource2(i)==1)), r=ray*s01+n;
elseif ((dsource1(i)==1) & (dsource2(i)==0)), r=s10*ray+n; else
r=s11*ray+n; end;
% The correlation metrics are computed below
c00=dot(r,s00); c01=dot(r,s01); c10=dot(r,s10); c11=dot(r,s11); % The decision on the ith symbol is made next c_max=max([c00,c01,c10,c11]);
if (c00==c_max), decis1=0; decis2=0; elseif (c01==c_max), decis1=0; decis2=1; elseif (c10==c_max), decis1=1; decis2=0; else decis1=1; decis2=1; end;
% Increment the error counter, if the decision is not correct symbolerror=0;
if (decis1~=dsource1(i)), numofbiterror=numofbiterror+1; symbolerror=1; end;
if (decis2~=dsource2(i)), numofbiterror=numofbiterror+1; symbolerror=1;
end;
if (symbolerror==1), numofsymbolerror=numofsymbolerror+1; end; end
counter=counter+1; end
ps=numofsymbolerror/(N*counter); % since there are totally N symbols
pb=numofbiterror/(2*N*counter); % since 2N bits are transmitted %文件3
function [pb1,ps1]=cm_sm32(snr_in_dB) % [pb,ps]=cm_sm32(snr_in_dB)
% CM_SM3 finds the probability of bit error and symbol error for % the given value of snr_in_dB, signal to noise ratio in dB. N=100;
E=1; % energy per symbol snr=10^(snr_in_dB/10); % signal to noise ratio sgma=sqrt(E/snr)/2; % noise variance s00=[1 0]; s01=[0 1]; s11=[-1 0]; s10=[0 -1]; % signal mapping % generation of the data source numofsymbolerror=0; numofbiterror=0; counter=0;
while(numofbiterror<100) for i=1:N,
temp=rand; % a uniform random variable between 0 and 1
if (temp<0.25), % with probability 1/4, source output is \
dsource1(i)=0; dsource2(i)=0;
elseif (temp<0.5), % with probability 1/4, source output is \
dsource1(i)=0; dsource2(i)=1;
elseif (temp<0.75), % with probability 1/4, source output is \
dsource1(i)=1; dsource2(i)=0;
else % with probability 1/4, source output is \
dsource1(i)=1; dsource2(i)=1; end; end;
% detection and the probability of error calculation
for i=1:N,
% the received signal at the detection, for the ith symbol,is:
n=sgma*randn(1,2); % 2 normal distributed r.v with 0, variance sgma
if ((dsource1(i)==0) & (dsource2(i)==0)), r=s00+n;
elseif ((dsource1(i)==0) & (dsource2(i)==1)), r=s01+n;
elseif ((dsource1(i)==1) & (dsource2(i)==0)), r=s10+n; else
r=s11+n; end;
% The correlation metrics are computed below
c00=dot(r,s00); c01=dot(r,s01); c10=dot(r,s10); c11=dot(r,s11); % The decision on the ith symbol is made next c_max=max([c00,c01,c10,c11]);
if (c00==c_max), decis1=0; decis2=0; elseif (c01==c_max), decis1=0; decis2=1; elseif (c10==c_max), decis1=1; decis2=0; else decis1=1; decis2=1; end;
% Increment the error counter, if the decision is not correct symbolerror=0;
if (decis1~=dsource1(i)), numofbiterror=numofbiterror+1; symbolerror=1; end;
if (decis2~=dsource2(i)), numofbiterror=numofbiterror+1; symbolerror=1; end;
if (symbolerror==1), numofsymbolerror=numofsymbolerror+1; end; end
counter=counter+1; end
ps1=numofsymbolerror/(N*counter); % since there are totally N symbols
pb1=numofbiterror/(2*N*counter); % since 2N bits are transmitted
附录
参考文献： 1、《MATLAB 宝典》 陈杰等编著 电子工业出版社 2、《MATLAB信号处理》 刘波, 文忠, 曾涯编著 北京电子工业出版社 3、《数字信号处理的MATLAB实现》 万永革编著 北京科学出版社 4、网上资料