bfsk.m

A detail Matlab simulation code example for BFSK performance

% MATLAB script for BFSK simulation
clear all;
SNRindB1=0:2:15;
for k=1:length(SNRindB1)

	snr_in_dB = SNRindB1(k);	% simulated error rate
	N=10000;
	Eb=1;
	d=1;				  
	snr=10^(snr_in_dB/10);	 	  	% signal to noise ratio per bit
	sgma=sqrt(Eb/(2*snr));	  	  	% noise variance

	phi=0;
	% generation of the data source follows
	dsource = randint(1,N);
	
	% detection and the probability of error calculation
	numoferr=0;
	for i=1:N,
	  % demodulator output
	  if (dsource(i)==0),
		r0c(i)=sqrt(Eb)*cos(phi)+sgma*randn;
		r0s(i)=sqrt(Eb)*sin(phi)+sgma*randn;
		r1c(i)=sgma*randn;
		r1s(i)=sgma*randn;
	  else
		r0c(i)=sgma*randn;
		r0s(i)=sgma*randn;
		r1c(i)=sqrt(Eb)*cos(phi)+sgma*randn;
		r1s(i)=sqrt(Eb)*sin(phi)+sgma*randn;
	  end;
	end
	  % square law detector outputs

	r0=r0c.^2+r0s.^2;
    r1=r1c.^2+r1s.^2;

	% decision is made next
	
	for i=1:N
		if (r0(i)>r1(i)),
			decis(i)=0;
		else
			decis(i)=1;
		end;
	end

	numoferr = sum(decis~=dsource);
	smld_err_prb(k)=numoferr/(N);

end

SNRindB2=0:0.1:15;
for i=1:length(SNRindB2)
  SNR=exp(SNRindB2(i)*log(10)/10);     	% signal to noise ratio
  theo_err_prb(i)=(1/2)*exp(-SNR/2);	% theoretical symbol error rate
end

% Plotting commands follow
semilogy(SNRindB1,smld_err_prb,'*');
hold
semilogy(SNRindB2,theo_err_prb);