estimator.m

OFDM的详细仿真代码

function [H_est , MSE] = estimator( Recv , Training , Method , N_subc_Remain , H_ideal)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 进行基本的LS和LS-DFT信道估计
% 如果仅输入两个参数, 则进行基本LS信道估计, 得到各子载波上的信道估计值.
% 如果使用全部的五个参数, 则可以进行LS和LS的DFT改进算法, 并调整信道估计器参数, 计算出
% 均方误差.

% 输入:   Recv, 频域接收到的各个子载波上的复数信号, N_subc(子载波数) 行, 1列的复数向量
%         Training , 发送的训练序列 , N_subc 行, 1 列的向量 
%                    注意: 训练序列中不能有零, 否则出错.
%         Method, 信道估计的方法 ,正整数,  1--- LS估计, 2 ---LS估计的DFT改进
%         N_subc_Remain, LS估计的DFT改进方法,所保留的子载波数. 为正整数值.
%                        建议选取改值等于最大多径时延对应的时域样点数
%
% 输出:   H_est, 估计得到的各个子载波上的频域响应, N_subc 行, 1列的复数向量
%         MSE, 本次估计的均方误差
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


N_subc = size(Recv,1);  % 子载波数
H_est = zeros(N_subc ,1);
% 接收信号乘上训练序列的共轭, 除以训练序列的模值的平方,得到LS估计的信道响应

H_ls = Recv.*conj(Training)./abs(Training).^2;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
% 如果仅输入两个参数
if nargin == 2   
    H_est = H_ls;   %  LS估计
    MSE = [];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%  
% 如果输入五个参数
elseif nargin == 5
    
    if  Method == 1 
        H_est = H_ls; %  LS估计
    
    elseif  Method == 2  %  LS估计DFT改进
        % 首先变换到时域
        time_domain =  ifft(fftshift(H_ls)) * sqrt(N_subc);
        time_cut = zeros(N_subc,1);
        leakage = 0;       % 能量泄漏的子载波数
        % 保留时域能量集中的N_subc_Remain个样点
        time_cut( 1: N_subc_Remain ) = time_domain( 1: N_subc_Remain );
        % 保留能量泄漏的leakage个样点
        time_cut( N_subc - leakage : N_subc ) = time_domain( N_subc - leakage : N_subc );
        % 变换到频域
        H_ls_dft = fftshift(fft(time_cut) * 1/sqrt(N_subc));
        H_est = H_ls_dft;
        
    else
        error('子程序estimator输入参数不匹配!');
    end
    
    % 计算均方误差
    diff = H_ideal - H_est;
    MSE =  sum( abs(diff).^2 ) / N_subc;
end