OMP信道估计基于OMP压缩感知的信道估计算法的MATLAB仿真

Posted 2022-03-28 fpga&matlab

1.软件版本

MATLAB2021a
2.本算法理论知识

3.核心代码

clc;
clear;
close all;
warning off;
addpath 'func\\'
 
CYC = 20;
for ij = 1:CYC
    ij
    CYC = 20;
    RandStream.setDefaultStream(RandStream('mt19937ar','seed',ij));
    Len                 = 8;
    Nc                  = 64*Len;%子载波数
    T                   = 6.4e-6;
    TG                  = 1.6e-6;
    fLen                = 512;
    I                   = 4;
    %导频坐标
    pilot_index         = [1:I:Nc];
    N                   = Nc;%总载波数
    [Rm,Cn]             = size(pilot_index);%导频子载波数
    %多普勒频移
    doppler_frequency   = 0.01;
    ts                  = 1e-6; 
    %保护时间
    CP                  = Nc/Len/(T/TG);
    C                   = 2; 
    SNR_dB              = [0:2:20];
    err_rate            = ones(C,length(SNR_dB));
    ERR_RATE            = ones(1,length(SNR_dB));
    ERR_RATE2           = ones(1,length(SNR_dB));
    ERR_RATE3           = ones(1,length(SNR_dB));
    h1                  = zeros(N,1);
    h2                  = zeros(N,1);
    %多径个数
    multipath_number = 3;
    delay            = [0,1e-6,2e-6]/ts;%各径延迟
    trms             = 4e-6/ts; %多径平均延迟
    var_pow          = 10*log10(exp(-delay/trms));
    RLchannel        = rayleighchan(1,doppler_frequency,delay,var_pow);
    RLchannel.StorePathGains = 1;
    test             = ones(C,1);%测试向量
    filter(RLchannel,test);
    %提取瑞利信道
    h_RL             = RLchannel.PathGains;
    for ii=1:C
        x_Trans = randint(N,1,4);
        %QPSK调制
        X       = func_QPSK_mod(x_Trans);
        %待传输信号
        x       = func_OFDM_mod(X,fLen,CP,Nc);     
        %信道
        for hh=1:multipath_number;
            h1(1+delay(hh))= h_RL(ii,hh);%信道的冲击响应
        end
        %H为根据22计算得到的H
        H   = fft(h1,fLen);
        %收到的信号
        y_r = filter(h1,1,x);
        for SNR_index=1:length(SNR_dB);
            %加噪声
            y       = awgn(y_r,SNR_dB(SNR_index),'measured'); 
            %去CP
            y0      = y(CP+1:CP+Nc,1);
            Y       = fft(y0);
            
            %你所要求的不太对的函数写法
            est_H        = ChannelEstimation(SNR_dB(SNR_index),1,delay,doppler_frequency,var_pow);
            %CS信道估计，H_esti为估计得到的H
            [H_esti,h2]  = func_omp(Y,X,Nc,fLen,pilot_index,multipath_number);
            %计算估计得到的Ap部分
            Ap   = abs(h2);
            
            %计算估计得到的exp部分
            exps = angle(h2);
            
            
            %估计的导频加信号的值
            X_esti  = Y./H_esti;
            x_omp_rec                           = func_QPSK_demod(X_esti);
            [err_number,err_rate(ii,SNR_index)] = symerr(x_Trans,x_omp_rec);
            err_num(ii,SNR_index)            = sum(sum(cov(x_Trans,x_omp_rec)));
            mse_num(ii,SNR_index)            = mse(abs(h1(1:multipath_number)-h2(1:multipath_number)));       
        end
    end
    for jj=1:length(SNR_dB);
        ERR_RATE(1,jj) = mean(err_rate(:,jj));
        ERR_RATE2(1,jj)= mean(err_num(:,jj));
        ERR_RATE3(1,jj)= mean(mse_num(:,jj));
    end
    S1 = [];
    S2 = [];
    S3 = [];
    
    if ij > 1
       load func\\tmps.mat
    end
    S1 = [S1;ERR_RATE];
    S2 = [S2;ERR_RATE2]; 
    S3 = [S3;ERR_RATE3]; 
    save func\\tmps.mat S1 S2 S3 SNR_dB
    addpath 'func\\'
end

load func\\tmps.mat
ERR_RATEs  = mean(S1,1);
ERR_RATE2s = mean(S2,1);
ERR_RATE3s = mean(S3,1);

figure;
plot(SNR_dB,ERR_RATE2s/max(ERR_RATE2s),'b-s');
hold on;
xlabel('SNR');
ylabel('信号相关性');
grid on;


figure;
semilogy(SNR_dB,ERR_RATEs,'b-s');
hold on;
xlabel('SNR');
ylabel('系统误码率');
grid on;


figure;
semilogy(SNR_dB,ERR_RATE3s,'b-s');
hold on;
xlabel('SNR');
ylabel('信道估计H 估计误差');
grid on;



save R.mat SNR_dB ERR_RATEs ERR_RATE2s ERR_RATE3s

%显示原始信道和估计后的信道
ho   = h1(1:multipath_number);
hest = h2(1:multipath_number); 

ho
hest

4.操作步骤与仿真结论

 5.参考文献

[1]赵锦航, 刘健均, 周思源,等. 基于BIC停止准则的改进A*OMP信道估计算法[J]. 计算机应用与软件, 2019, 36(5):6.

[2]朱芹, 王彪. 基于改进BOMP算法的水声信道估计[J].  2022(8).

 A01-102
6.完整源码获得方式

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