rayleigh2.m

该系统主要使用matlab实现了stbc2*1系统的发送和接收

%--------------------------------------------------------------------
%	z=rayleigh2(t,fd,N,phase0)
%	-------------------
%	- generating multiple uncorrelated Rayleigh fading waveforms 
%	using the modified Jakes' model with unity variance
%	- input:
%		t      --- a real time vector
%		fd     --- maximum doppler frequency in Hz
%		N      --- number of fading waveforms to be generated, 
%			   it must be a power of 2.
%		phase0 --- an initial phase vector with 8 elements 
%			   when N < 8; otherwise, with N elements.
%			   (optional)
%	- output:
%		z    --- a complex matrix with N columns which are
%			 N uncorrelated fading waveforms
%	- note:
%		In this program, the parameter N0 in the model is 8 
%		when N < 8 or N otherwise in default. 
%---------------------------------------------------------------------

%---------------------------------------------------------------------
%$	generating multiple uncorrelated Rayleigh fading waveforms
%   Dependencies:
%	fwht.m
%   Compatability:
%	Matlab Ver 3.5g, Ver 4.1a
%   Notes:
%   References: P. Dent,"Jakes Fading Model Revisited", Electronics
%		letters, 24th, June, 1993, Vol.29, No.13
%
%----------------------------------------------------------------------

function z=rayleigh2(t,fd,N,phase0)

	p=log2(N)-floor(log2(N));

	if p~=0 
		error('The third argument must be a power of 2');
	elseif N < 8 
		N0=8;
	else 
		N0=N;
	end
    
	M=4*N0;
	wm=2.0*pi*fd;
	tl=length(t);
	n=1:N0;

	if nargin < 4
		phase0=2*pi*rand(1,N0);
	end

	time=(ones(N0,1)*t)';
	wn=ones(tl,1)*(wm*cos(2.0*pi*(n-0.5)/M));
	beta=ones(tl,1)*(pi*n/N0);
	cita0=ones(tl,1)*phase0;

	xc=zeros(tl,N0);
	xs=xc;
	y=xc;

	xc=cos(beta).*cos(wn.*time+cita0);	
	xs=sin(beta).*cos(wn.*time+cita0);	
	y=sqrt(2/N0)*(xc+j*xs);

	m=N0/N;
	if m~=1
		g=reshape(n,N,m);
		y=y';
		u=zeros(N,tl);
		for k=1:N
			u(k,:)=sum(y(g(k,:),:));
		end
		z=N*(fwht(u))';
	else
     
      z=N0*(fwht(y'))';
      
   end

   %Get the histograms of time difference between y(t) and y(t-1)
%   Y = y(:,1) - wshift('1D',y(:,1),-1); Y(1) = []; Y = real(Y);
%   Z = z(:,1) - wshift('1D',z(:,1),-1); Z(1) = []; Z = real(Z);
%   subplot(2,1,1); hist(Y,50);
%   subplot(2,1,2); hist(Z,50);
   
   
return