www.gusucode.com > 基于Matlab的MIMO通信系统仿真 含报告；司中威；了解移动通信 > 基于Matlab的MIMO通信系统仿真 含报告；司中威；了解移动通信关键技术，了解数字通信系统仿真流程，实现基本的信道编译码、调制解调等通信模块。（好评如潮，课设拿满） 学习并实现MIMO空时处理技术 学习性能分析的思路和方法/mimo/matlab for mimo 2x2/channel_sim.m

    % Channel
% By Maxime Maury
% 05-04-22

clear all;
close all;

disp('Start channel_sim')

load('TXOutput');
load('tx_param');

% Length of the stream
channel_len = size(Channel1,2);

% Downconvert from 10 kHz to 0 Hz
Channel1dn = [ upconv_cos(Channel1, Fc_tx, Fs, 0, 0) + j* upconv_sin(Channel1, Fc_tx, Fs, 0, 0)];    
Channel2dn = [ upconv_cos(Channel2, Fc_tx, Fs, 0, 0) + j* upconv_sin(Channel2, Fc_tx, Fs, 0, 0)];    
[b,a] = cheby2(8,16, (2.47/2*Fc/Fs)*2,'low');
Channel1dn = filter(b,a,Channel1up);
Channel2dn = filter(b,a,Channel2up);

% Multiplying 2 times by cos lower half the amplitude of the signal
Channel1dn = 2 * Channel1dn;
Channel2dn = 2 * Channel2dn;

% Channel Matrix
% H = sqrt(1/2)*ones(4,2);
H = [1 0; 1 0; 0 1; 0 1];
% H = sqrt(1/2)*randn(4,2) + j*sqrt(1/2)*randn(4,2);
% H =[-0.8247+0.0672i  -0.2265-0.5771i;
   1.2417-0.5251i  -1.1163-0.8573i;
   0.0160+0.1416i  -0.3327+0.0468i;
  -0.3825+0.3055i   1.1659+0.6654i];

% Generate the data streams at the receive antennas
S = [Channel1up; Channel2up];

% Where the frames start
frame_start = init_len + time_end + 1;

% There is a sinusoid of length time_end + 1
Y = H*S(:,1:frame_start-1);


% Proceed frame by frame
for fr = 1:nr_frames
    % H = H + 1/1000*(sqrt(1/2)*randn(4,2) + j*sqrt(1/2)*randn(4,2));
    Y = [Y H*S(:,(fr-1)*Lf + frame_start:fr*Lf+frame_start + 1)];
end

Y = [Y H*S(:,fr*Lf+frame_start+2:end)];

% AWGN
SNR_dB = 34; %dB

% Compute Es
s = frame_start;
e = s + Lf*nr_frames - 1;

% plot(abs(Channel1up(1,s:e)));

Es = sum(abs(Channel1up(1,s:e))^2)/((e-s+1)/L);

figure;
Nc = 2;
Nr = 2;

subplot(Nr,Nr,1);
plot(Channel1up(1, frame_start-1),'r');
hold on;
plot(Channel1up(:,(fr-1)*Lf + frame_start:fr*Lf+frame_start + 1));

sigma_sqr = Es / 10^(SNR_dB/10);

Noise = sqrt(sigma_sqr/2) * ( randn(4,channel_len) + j*randn(4,channel_len));
Y_n = Y + Noise;

% Upconvert
for k=1:4
    Y_R(k,:) = upconv(real(Y_n(k,:)), imag(Y_n(k,:)), Fc_tx, Fs, 0);
end

% figure('Name','Channel')
% plot(Channel1(:),'r');%
% hold on;
% plot(Y_R(1,:),'g')
% legend('Channel1', 'Channel A=1')

deviation = std(Y_n(1,:)-Y(1,:));

SNR = 10*log10(Es/(deviation^2))

save('ChannelOutput','Y_R');

disp('End')

% figure('Name','Low Pass Filter');
% freqz(b,a,512,Fs);