cm_sm34.m

contemporarycommunicatonsystem－using MATLAB经典书目源程序！

function [p]=cm_sm34(snr_in_dB)
% [p]=cm_sm34(snr_in_dB)
%		CM_SM34  finds the probability of error for the given
%   		value of snr_in_dB, signal to noise ratio in dB.
N=10000;
E=1;				  	% energy per symbol
snr=10^(snr_in_dB/10);	 	  	% signal to noise ratio
sgma=sqrt(E/(4*snr));	  	  	% noise variance
% generation of the data source follows
for i=1:2*N,	
  temp=rand;			  	% a uniform random variable between 0 and 1
  if (temp<0.5),		  
    dsource(i)=0;		  	% with probability 1/2, source output is "0"
  else
    dsource(i)=1;		  	% with probability 1/2, source output is "1"
  end;
end;
% Differential encoding of the data source follows
mapping=[0 1 3 2];
M=4;
[diff_enc_output] = cm_dpske(E,M,mapping,dsource);
% received signal is then
for i=1:N,
  [n(1) n(2)]=gngauss(sgma);
  r(i,:)=diff_enc_output(i,:)+n;
end;
% detection and the probability of error calculation
numoferr=0;
prev_theta=0;
for i=1:N,
  theta=angle(r(i,1)+j*r(i,2));
  delta_theta=mod(theta-prev_theta,2*pi);
  if ((delta_theta<pi/4) | (delta_theta>7*pi/4)),
    decis=[0 0];
  elseif (delta_theta<3*pi/4),
    decis=[0 1];
  elseif (delta_theta<5*pi/4)
    decis=[1 1];
  else
    decis=[1 0];
  end;
  prev_theta=theta;
  % increase the error counter, if the decision is not correct
  if ((decis(1)~=dsource(2*i-1)) | (decis(2)~=dsource(2*i))),
    numoferr=numoferr+1;
  end;
end;
p=numoferr/N;