📄 ctlmmse.asv
字号:
clc
clear all
Nt = 1; % the number of transmitted antennas
Nr = 1; % the number of transmitted antennas
T=2:2:24; % the number of symbol periods
Tp=Nt;
Td=T-Tp;
SNR = 10; % the system signal-to-noise ratio with dB
snr = 10.^(0.1*SNR); % the signal-to-noise with normal scale
snrp=snr;
MM=100; % 1000 channel
NN = 100;% using 10000 Monte-Carlo runs
hm=zeros(Nt*Nr,1); % channel mean
hh=eye(Nt*Nr); % channel covariance
vv=eye(Tp*Nr); % noise covariance
% nn=eye(Td*Nr); % noise covariance
capa_ray = zeros(1,length(T)); % rayleigh fading with perfect csi and without training symbol
capa1 = zeros(1,length(T)); % perfect csi
capa2 = zeros(1,length(T)); % worst case noise lower bound
capa3 = zeros(1,length(T)); % inequality lower bound
capa30=zeros(1,length(T));
capa300=zeros(1,length(T));
for ii = 1:length(T)
waitbar(ii/length(T));
A_ray=zeros(T(ii)*Nr,T(ii)*Nr); % rayleigh fading with perfect csi and without training symbol
% capa1 = zeros(1,length(T)); % perfect csi
A10=zeros(Td(ii)*Nr,Td(ii)*Nr);
%capa2 = zeros(1,length(T)); % worst case noise lower bound
A20=zeros(Td(ii)*Nr,Td(ii)*Nr);
AA20=zeros(Td(ii)*Nr,Td(ii)*Nr);
% capa3 = zeros(1,length(T)); % inequality lower bound
% capa30=zeros(1,length(T));
% capa300=zeros(1,length(T));
A30=zeros(Td(ii)*Nr,Td(ii)*Nr);
AA30=zeros(Td(ii)*Nr,Td(ii)*Nr);
aa300=0;
% LMMSE estimator
p=eye(Nt*Nr); % training symbol
pp=inv(p'*p)*p'; % wei ni
F=sqrt(snrp)*hh*p'*inv(snrp*p*hh*p'+vv');
f0=(eye(size(F*pp))-sqrt(snrp)*F*pp)*hm;
nn=eye(Td(ii)*Nr); % noise covariance
nn_ray=eye(T(ii)*Nr); % rayleigh fading with perfect csi and without training symbol
for jj=1:MM
Hw=sqrt(1/2)*(randn(Nr*Nt,1) + j*randn(Nr*Nt,1)); % channel
v=sqrt(1/2)*(randn(Nr*Tp,1) + j*randn(Nr*Tp,1)); % training noise
z=sqrt(snrp)*p*Hw+v; % receive
g=F*z+f0; % estimation
% B=zeros(Nt*Nr);
B=eye(Nt*Nr);
C=inv(eye(Nt*Nr)+snrp*hh*p'*inv(vv)*p);
d=B*g+C*hm-B*f0;
for kk =1:NN
X_ray =sqrt(1/(2*Nt))* (randn(Nt,T(ii)) + j* randn(Nt,T(ii))); % rayleigh fading with perfect csi and without training symbol
XX_ray=kron(X_ray.',eye(Nr));
X =sqrt(1/(2*Nt))* (randn(Nt,Td(ii)) + j* randn(Nt,Td(ii)));
XX=kron(X.',eye(Nr));
A_ray=A_ray+XX_ray*Hw*Hw'*XX_ray'; % rayleigh fading with perfect csi and without training symbol
A10=A10+XX*Hw*Hw'*XX'; % perfect csi
A20=A20+XX*d*d'*XX'; % worst case noise lower bound
AA20=AA20+snr*XX*C*hh*XX'+nn;
A30=A30+XX*Hw*Hw'*XX'; % inequality lower bound
aa300=aa300+1/T(ii)*log2(det(eye(Nt*Nr)+snr*XX'*inv(nn)*XX*C*hh));
end
A_ray=1/NN*A_ray; % rayleigh fading with perfect csi and without training symbol
capa_ray(ii)=capa_ray(ii)+1/T(ii)*log2(det(eye(T(ii)*Nr)+snr*A_ray*inv(nn)));
A10=1/NN*A10; % perfect csi
capa1(ii)=capa1(ii)+1/T(ii)*log2(det(eye(Td(ii)*Nr)+snr*A10*inv(nn)));
A20=1/NN*A20; % worst case noise lower bound
AA20=1/NN*AA20;
capa2(ii)=capa2(ii)+1/T(ii)*log2(det(eye(Td(ii)*Nr)+snr*A20*inv(AA20)));
A30=1/NN*A30; % inequality lower bound
capa30(ii)=capa30(ii)+1/T(ii)*log2(det(eye(Td(ii)*Nr)+snr*A30*inv(nn)));
aa300=1/NN*aa300;
capa300(ii)=aa300+capa300(ii);
end
capa_ray(ii)=1/MM*capa_ray(ii); % rayleigh fading with perfect csi and without training symbol
capa1(ii)=1/MM*capa1(ii);
capa2(ii)=1/MM*capa2(ii);
capa3(ii)=1/MM*(capa30(ii)-capa300(ii));
ww= waitbar(ii/length(T));
end
close(ww)
% figure
plot(T,capa_ray,'ko-')
hold on
plot(T,capa1,'ks-')
hold on
plot(T,capa2,'kv-')
hold on
plot(T,capa3,'k*-')
hold on
grid on
title('The Ergodic Capacity of MIMO Systems')
xlabel('T [channel use]')
ylabel('Ergodic Capacity [bit/channel use]')
legend('perfect csi','worst case','inequality')
⌨️ 快捷键说明
复制代码
Ctrl + C
搜索代码
Ctrl + F
全屏模式
F11
切换主题
Ctrl + Shift + D
显示快捷键
?
增大字号
Ctrl + =
减小字号
Ctrl + -