B. P. Lathi, Zhi Ding - Modern Digital and Analog Communication Systems-Oxford University Press (2009)

10.12 MATLAB Exercises 601
noiseq=randn(L,2) ;
BER= [ ];
BER_az= [ ];
% Generating the channel noise (AWGN )
for i=l :12,
Eb2N (i)=i ; %(Eb/N in dB )
Eb2N_num=10 (Eb2N(i) /10) ; % Eb/N in numeral
Var_n=l/ (2*Eb2N_num) ;
%1/SNR is the noise variance
signois=sqrt (Var_n) ;
% standard deviation
awgnois=signois* (noisei+j *noiseq) ; % AWGN complex channels
% Add noise to signals at the channel output
ychout=xmodsig+awgnois;
% Non-coherent detection
ydiml=abs (ychout (:,1));
ydim2 =abs (ychout (:,2 ));
dec= (ydiml>ydim2 );
% Compute BER from simu lation
BER= [BER; sum(dec~=s_data) /L] ;
% Compare against analytical BER .
BER_az= [BER_az ; 0.5* exp (-Eb2N_num/2) ];
end
figber=semilogy (Eb2N, BER_az , 'k-',Eb2N, BER, 'k- o') ;
set ( figber , 'Linewidth ' , 2) ;
legend('Analytical BER' , 'Noncoherent FSK simulation' );
fx=xlabel ('E_b /N (dB) ');
fy=ylabel ('Bit error rate' );
set (fx, 'FontSize' , 11) ; set (fy, 'Fontsize' , 11) ;
COMPUTER EXERCISE 10.5: NONCOHERENT DETECTION OF BINARY
DIFFERENTIAL PSK
To test the results of a binary differential phase shift keying system, we present MATLAB program
Exl 0_5 . m. As in previous cases, the measured BER results in Figure 10.52 matches the analytical BER
results very well.
% MATLAB PROGRAM <Exl0 5.m>
% This program provides simulation for dif ferential detection of
% binary DPSK . Dif ferential detetion only needs to compare the
% successive phases of the signal samples at the receiver
%
clear;clf
L=l000000;
%Number of data symbols in the simulation
s_data=round (rand (L, l) );
% Generating initial random phase
initphase= [2*rand] ;
% dif ferential modulation
s_denc=mod (cumsum ( [0;s_data] ) ,2) ;
% define the phase divisible by pi
xphase=initphase+s_denc ;
clear s_denc ;
% modulate the phase of the signal
xmodsig=exp (j*pi*xphase); clear xphase;