资源简介
MIMO-OFDM不同信道估计的对比(matlab代码)很不错的东西
代码片段和文件信息
%------------------------------------------
% EE359 final project Fall 2002
% Channel estimation for a MIMO-OFDM system
% By Shahriyar Matloub
%------------------------------------------
clear all;
%close all;
i=sqrt(-1);
Rayleigh=1;
AWGN=0; % for AWGN channel
MMSE=0; % estimation technique
Nsc=64; % Number of subcarriers
Ng=16; % Cyclic prefix length
SNR_dB=[0 5 10 15 20 25 30 35 40]; % Signal to noise ratio
Mt=2; % Number of Tx antennas
Mr=2; % Number of Rx antennas
pilots=[1:Nsc/Ng:Nsc]; % pilot subcarriers
DS=5; % Delay spread of channel
iteration_max=200;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Channel impulse response %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if (Rayleigh)
N=50;
fm=100;
B=20e3;
fd=(rand(1N)-0.5)*2*fm;
theta=randn(1N)*2*pi;
c=randn(1N);
c=c/sum(c.^2);
t=0:fm/B:10000*fm/B;
Tc=zeros(size(t));
Ts=zeros(size(t));
for k=1:N
Tc=c(k)*cos(2*pi*fd(k)*t+theta(k))+Tc;
Ts=c(k)*sin(2*pi*fd(k)*t+theta(k))+Ts;
end
r=ones(Mt*Mr1)*(Tc.^2+Ts.^2).^0.5;
index=floor(rand(Mt*MrDS)*5000+1);
end
MEE1=zeros(1length(SNR_dB));
MEE2=zeros(1length(SNR_dB));
for snrl=1:length(SNR_dB)
snrl
estimation_error1=zeros(Mt*MrNsc);
estimation_error2=zeros(Mt*MrNsc);
R1=besselj(02*pi*fm*(Nsc+Ng)/B);
sigma2=10^(-SNR_dB(snrl)/10);
aa=(1-R1^2)/(1-R1^2+sigma2);
bb=sigma2*R1/(1-R1^2+sigma2);
for iteration=1:iteration_max
%iteration
if AWGN==1
h=ones(Mt*Mr1);
else
phi=rand*2*pi;
h=r(index+iteration)*exp(j*phi);
%h=rand(Mt*MrDS);
h=h.*(ones(Mt*Mr1)*(exp(-0.5).^[1:DS]));
h=h./(sqrt(sum(abs(h).^22))*ones(1DS));
end
CL=size(h2); % channel length
data_time=zeros(MtNsc+Ng);
data_qam=zeros(MtNsc);
data_out=zeros(MrNsc);
output=zeros(MrNsc);
for tx=1:Mt
data_b=0*round(rand(4Nsc)); % data
data_qam(tx:)=j*(2*(mod(data_b(1:)+data_b(2:)2)+2*data_b(1:))-3)+...
2*(mod(data_b(3:)+data_b(4:)2)+2*data_b(3:))-3;
for loop=1:Mt
data_qam(txpilots+loop-1)=(1+j)*(loop==tx); % pilots
end
data_time_temp=ifft(data_qam(tx:));
data_time(tx:)=[data_time_temp(end-Ng+1:end) data_time_temp];
end
for rx=1:Mr
for tx=1:Mt
output_temp=conv(data_time(tx:)h((rx-1)*Mt+tx:));
output(rx:)=output_temp(Ng+1:Ng+Nsc)+output(rx:);
end
np=(sum(abs(output(rx:)).^2)/length(output(rx:)))*sigma2;
noise=(randn(size(
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