rayleigh_fading.m

多用户检测器的matlab仿真模型

function [zz, z,z_dB] = rayleigh_fading(f_D, t, f_s)
% function [Ts, z_dB] = rayleigh_fading(f_D, t, f_s)
% generates a Rayleigh fading signal for given Doppler frequency f_D
% during the time period [0,t], with sampling frequency f_s >= 1000Hz.
%
% Input(s)
%   -- f_D  : [Hz] [1x1 double] Doppler frequency
%   -- t    : simulation time interval length, time interval [0,t]
%   -- f_s  : [Hz] sampling frequency, set to 1000 if smaller.
% Output(s)
%   -- Ts   : [Sec][1xN double] time instances for the Rayleigh signal
%   -- z_dB : [dB] [1xN double] Rayleigh fading signal

% Required parameters
if f_s < 1000;
    f_s=1000;               % [Hz]  Minimum required sampling rate
end;
N = ceil(t*f_s);            % Number of samples
% Ts contains the time instances at which z_dB is specified
Ts = linspace(0,t,N);

if mod(N,2)==1
    N=N+1;                  % Use even number of samples in calculation
end
f = linspace(-f_s, f_s, N); % [Hz]  Frequency samples used in calculation

% Generate complex Gaussian samples with line spectra in frequency domain
% Inphase :
Gfi_p = randn(2,N/2);
CGfi_p = Gfi_p(1,:)+i*Gfi_p(2,:);
CGfi = [conj(fliplr(CGfi_p)) CGfi_p ];
% Quadrature :
Gfq_p = randn(2,N/2);
CGfq_p = Gfq_p(1,:)+i*Gfq_p(2,:);
CGfq = [conj(fliplr(CGfq_p)) CGfq_p ];

% Generate fading spectrum, this is used to shape the Gaussian line spectra
omega_p = 1;    % This makes sure that the average received envelop can be 0dB
S_r = omega_p/4/pi./(f_D*sqrt(1-(f/f_D).^2));

% Take care of samples outside the Doppler frequency range, let them be 0
idx1 = find(f>f_D);
idx2 = find(f<-f_D);
S_r(idx1)=0;
S_r(idx2)=0;

% Generate r_I(t) and r_Q(t) using inverse FFT:
r_I = N*ifft(CGfi.*sqrt(S_r));
r_Q = -i*N*ifft(CGfq.*sqrt(S_r));

% Finally, generate the Rayleigh distributed signal envelope
zz=r_I+r_Q;
z = sqrt(abs(r_I).^2+abs(r_Q).^2);
z_dB = 20*log10(z);

% Return correct number of points
z_dB = z_dB(1:length(Ts));