suzuki.asv

suzuki过程的matlab仿真

%  Suzuki fading channel
% MEDS 精确多普勒扩展法 确定瑞利过程的同相分量
var1=1;
N_1=30;
fmax1=91;
sigma1=sqrt(var1);
n1=1:N_1
f_1=fmax1*sin(pi*(n1-0.5)/(2*N_1));
c_1=sigma1*sqrt(2/N_1)*ones(size(n1));
c_1=c_1/sqrt(2);
theta_1=rand(N_1,1)*2*pi;
% MEA 等面积法 确定瑞利过程的正交分量
var2=1;
N_2=20;
fmax2=100;
sigma2=sqrt(var2);
n2=1:N_2
f_2=fmax2*sin(pi*n2/(2*N_2));
c_2=sigma2*sqrt(2/N_2)*ones(size(n2));
c_2=c_2/sqrt(2);
theta_2=rand(N_2,1)*2*pi;
%MEDS生成均值为0，方差为1的对数正态阴影的参数
N_3=40;
var3=2;
fc=10;
sigma3=sqrt(var3);
n3=1:N_3
f_3=fc/sqrt(log(2))*erfinv((2*n3-1)/(2*N_3));
c_3=sigma3*sqrt(2/N_3)*ones(size(n3));
theta_3=rand(N_3,1)*2*pi;
g=(2*pi*fc/sqrt(2*log(2)))^2;

%生成莱思过程
A_Los=2;
f_Los=20;
theta_Los=pi;
T_interval=0.001;
T=1;
rice_t=Rice_generator(c_1,f_1,theta_1,c_2,f_2,theta_2,A_Los,f_Los,theta_Los,T_interval,T);
plot(t,rice_t)

%生成对数正态过程
m3=0;
lognormal_t=exp(Gauss_generator(c_3,f_3,theta_3,T_interval,T)*sigma3+m3);
%plot(t,log(lognormal_t));
%axis([0,10000,-1000,100])
% 生成suzuki过程
Suzuki_t=rice_t.*lognormal_t;
%plot(Suzuki_t)