%  Figure 6.35  CDMA pn code correlated with itself and a delayed version

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%   Nchips	 -- number of chips 
%   nsamples	 -- number of samples per chip.       
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Nchips = 32;
nsamples = 12;

CDMA = [];

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%  Generate code        
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
a = sign(randn(1,Nchips));


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%  Sample codes nsamples times per chip  				
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for i=1:length(a),
	CDMA = [CDMA,a(i)*ones(1,nsamples)];
end
CDMA1=[CDMA zeros(1,36)];
CDMA2=[zeros(1,16) CDMA zeros(1,20)];
t=(0:length(CDMA1)-1)*2/(length(CDMA1)-1);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%  Correlate CDMA1 with itself and with CDMA2					
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
R1=sum(CDMA1.*CDMA1)
R2=sum(CDMA1.*CDMA2)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%  Plotting the CDMA waveforms 						
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
figure;
subplot(2,1,1)
plot (t,CDMA1,'k');
axis([0 2 -1.2 1.2])
xlabel('time \muSec')
title('Waveform with 0 excess delay')
subplot(2,1,2)
plot(t,CDMA2,'k');
axis([0 2 -1.2 1.2])
xlabel('time \muSec')
title('Waveform with 1.3\tau excess delay')