OFDM系统中固定频偏算法

matlab的旋律

加入固定频偏：
function berMatrix = freqOffsetOFDM(BPS,NS,M,SNR,ifftsize,carriers,N,ep)

%标准OFDM系统
input_bit_stream= sign(randn(1,BPS*NS));
input_bit_stream(input_bit_stream== -1)=0;
parallel_data = StoP(input_bit_stream ,M);% 串并转换
%QAM调制
modulated_data =qammod(parallel_data,M);
berMatrix = zeros(size(SNR));
for m=1:length( SNR)  %信噪比变量
    k  = 1 ;
    for n = 1 : NS%OFDM信号序数变量
        ofdm_symbol = zeros(1 ,ifftsize);
        ofdm_symbol(carriers) = modulated_data(k: k+N-1);  %各子信道加载数据
        %IFFT转换成时域信号
        tx_signal = ifft(ofdm_symbol ,ifftsize);
        %信道
        %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
        %加入频域频移
        rx_signal = tx_signal.*exp((2*1i*pi*ep/ifftsize).*(0:ifftsize-1));
        %加入噪声
        rx_signal=awgn(rx_signal,SNR(m),'measured');
        %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
        received_ofdm  = fft(rx_signal, ifftsize); %FFT转换成各自通道数据
        received_symbols(k:k+N-1) = received_ofdm(carriers); %去掉循环前缀
        k  = k +N ;
    end  %OFDM信号序数变量结束

    %received_symbols：接收端FFT后得到的各子通道的复数据，
    %          直接画得到星座图
    %          %figure
    %          subplot(1,4,ll)
    %          plot(received_symbols,'*');
    %          axis([-log2(M),log2(M),-log2(M),log2(M)]);
    %          title(['\epsilon=' num2str(ep)] );

    %接收端对M进制复数据解调，得到M进制码元
    received_data =qamdemod(received_symbols,M);
    output_bit_stream = PtoS(received_data, M);%M进制转换为二进制码元
    berMatrix(m)= sum(xor(input_bit_stream, output_bit_stream))/length(input_bit_stream);%计算误码率
end %信噪比变量结束


对加频偏信号进行ICI自消除：
function berMatrix = freqOffsetOFDMICI(BPS,NS,M,SNR,ifftsize,carriers,N,ep)

%ICI自消除法
% Input Bit Stream  is normally Distributed
input_bit_stream= sign(randn(1,BPS*NS));
input_bit_stream(input_bit_stream== -1)=0;
parallel_data = StoP(input_bit_stream ,M);
modulated_data =qammod(parallel_data,M);%QAM调制
%奇偶载波序列定义
odd_carriers = carriers(1:2: N-1);
even_carriers = carriers(2:2: N);

berMatrix = zeros(size(SNR));
for m=1:length(SNR) %信噪比变量
    k = 1;
    for n = 1:NS   %OFDM信号序数变量
        ofdm_symbol1 = zeros(1,ifftsize);
        ofdm_symbol2 = zeros(1,ifftsize);
        ofdm_symbol1(odd_carriers) = modulated_data(k: k+N/2-1);
        ofdm_symbol1(even_carriers) = -modulated_data(k: k+N/2-1); %奇通道数据取反
        ofdm_symbol2(odd_carriers) = modulated_data(k+N/2: k+N-1);
        ofdm_symbol2(even_carriers) = -modulated_data(k+N/2:k+N-1); %奇通道数据取反
        %发送端时域信号
        tx_signal1 = (ifft(ofdm_symbol1,ifftsize));
        tx_signal2 = (ifft(ofdm_symbol2,ifftsize));
        %信道
        %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
        %加入频移
        rx_signal1 = tx_signal1.*exp(1i*pi*ep/ifftsize*(0:ifftsize-1));
        rx_signal2 = tx_signal2.*exp(1i*pi*ep/ifftsize*(0:ifftsize-1));
        %加入噪声
        rx_signal1 = awgn(rx_signal1, SNR(m),'measured');
        rx_signal2 = awgn(rx_signal2, SNR(m),'measured');
        %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
        % 接收端FFT
        received_ofdm1 = fft(rx_signal1, ifftsize);
        received_ofdm2 = fft(rx_signal2, ifftsize);
        demod_sym1 = .5*(received_ofdm1(odd_carriers)-received_ofdm1(even_carriers));%前半个OFDM信号
        demod_sym2 = .5*(received_ofdm2(odd_carriers)-received_ofdm2(even_carriers));%后半个OFDM信号
        received_ofdm3 = [demod_sym1 demod_sym2];
        received_symbols(k:k+N-1) = received_ofdm3;
        k = k + N;
    end %OFDM信号序数变量结束
    received_data =qamdemod(received_symbols,M);%接收端对M进制复数据解调，得到M进制码元
    output_bit_stream = PtoS(received_data, M);%M进制转换为二进制码元
    berMatrix(m)= sum(xor(input_bit_stream, output_bit_stream))/length(input_bit_stream); %计算误码率
end %信噪比变量结束

极大似然估计法和改进算法
function berMatrix = freqOffsetOFDMMSL(BPS,NS,M,SNR,ifftsize,carriers,N,ep,N_awgn)

%极大似然估计法和改进算法
input_bit_stream= sign(randn(1,BPS*NS));
input_bit_stream(input_bit_stream== -1)=0;
parallel_data = StoP(input_bit_stream ,M);% 串并转换
modulated_data =qammod(parallel_data,M);%QAM调制
berMatrix = zeros(size(SNR));
for m=1:length(SNR)  %信噪比变量
    %计算ep-SNR对应的频偏
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    ofdm_symbol = zeros(1,ifftsize);
    ofdm_symbol(carriers(1:N/2)) = modulated_data(1:N/2);   %Use only half the data for MLE
    tx_signal1 = ifft(ofdm_symbol,ifftsize/2);     %对前一半通道的数据进行ifft_size/2的IFFT
    tx_signal = [tx_signal1,tx_signal1];           %复制前一半OFDM信号，形成一个完整的发送信号

    %信道
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %加入频移
    rx_signal = tx_signal.*exp((2*1i*pi*ep/ifftsize).*(0:ifftsize-1));
    %加入噪声
    %极大似然估计法：N_awgn=1；
    %修正算法：N_awgn>1;
    noise=0;
    for n_awgn=1:N_awgn
        %加入高斯白噪声
        noise=noise+awgn(rx_signal,SNR(m),'measured');
    end
    noise=noise/N_awgn;
    rx_signal = rx_signal + noise;
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %接收端对前后两时域序列分别进行FFT
    received_ofdm1 = fft(rx_signal(1:ifftsize/2), ifftsize/2);
    received_ofdm2 = fft(rx_signal((ifftsize/2)+1:ifftsize), ifftsize/2);

    %对频偏进行极大似然估计
    temp=0;temp1=0;
    for w=1:length(ifftsize/2)
        temp=temp + imag(received_ofdm2(w)*conj(received_ofdm1(w)));
        temp1=temp1 + real(received_ofdm2(w)*conj(received_ofdm1(w)));
    end
    epestMLE(m) = (atan(temp/temp1))/(pi);

    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %完成ep-SNR对应的频偏估计
    %以后接收到的OFDM信号直接用估计值校正
    k = 1;
    for n = 1:NS  %OFDM信号序数变量
        ofdm_symbol = zeros(1,ifftsize);
        ofdm_symbol(carriers(1:N)) = modulated_data(k:k+N-1);   %各子信道加载数据
        tx_signal = ifft(ofdm_symbol,ifftsize);%IFFT转换成时域信号

        %信道
        %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
        rx_signal = tx_signal.*exp((2*1i*pi*ep/ifftsize).*(0:ifftsize-1));%加入频域频移
        rx_signal=awgn(rx_signal,SNR(m),'measured');%加入噪声
        %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
        %利用第一次估计出的频偏进行校正
        received_ofdm = rx_signal.* exp((-2*1i*pi*epestMLE(m)/ifftsize)*(0:ifftsize-1));
        car_data= fft(received_ofdm,ifftsize); %FFT转换成各自通道数据
        received_symbols(k:k+N-1)=car_data(carriers(1:N)); %去掉循环前缀
        k = k + N;
    end %OFDM信号序数变量结束
    received_data =qamdemod(received_symbols,M);%接收端对M进制复数据解调，得到M进制码元
    output_bit_stream = PtoS(received_data, M); %M进制转换为二进制码元
    berMatrix(m)= sum(xor(input_bit_stream, output_bit_stream))/length(input_bit_stream); %计算误码率

end %信噪比变量结束

M进制转换为二进制码元：
function y=PtoS(received_data, M)

%M进制转换为二进制码元
M=log2(M);
[m,n]=size(received_data);
y=zeros(1,M*n);
for k1=1: n
    for k2=1: M
        if(received_data(k1)>=2^(M-k2))
            y(M*(k1-1)+k2)=1;
            received_data(k1)=received_data(k1)-2^(M-k2);
        else
            y(M*(k1-1)+k2)=0;
        end
    end
end


串并转换：
function y=StoP(input_bit_stream ,M)

% 串并转换
M=log2(M);
n=length(input_bit_stream);
y=zeros(1,n/M);
for k1=1: n/M
    y(k1)=0;
    for k2=1: M
        y(k1)=y(k1)+input_bit_stream((k1-1)*M+k2)*2^(M-k2);
    end
end

调用函数的脚本程序如下：
clear
close all
clc

SNR=0:2:25; % 信噪比
NS = 1600; % NS：待传送OFDM信号总个数
M = 8;% M：调制进制
N = 60; % 子通道个数
BPS = N*log2(M); % 一个OFDM信号携带的比特数

carriers = (1:N );  % 子通道序数
ifftsize =  128; %FFT长度

%未加频偏，未采用消除方法时
ep = 0 ;%归一化频偏
berMatrix_NOEP_Non = freqOffsetOFDM(BPS,NS,M,SNR,ifftsize,carriers,N,ep);
%加频偏,未采用消除方法时
ep = 0.05;%归一化频偏
berMatrix_EP_Non = freqOffsetOFDM(BPS,NS,M,SNR,ifftsize,carriers,N,ep);
berMatrix_EP_ICI = freqOffsetOFDMICI(BPS,NS,M,SNR,ifftsize,carriers,N,ep);

N_awgn = 1;
berMatrix_EP_SL = freqOffsetOFDMMSL(BPS,NS,M,SNR,ifftsize,carriers,N,ep,N_awgn);

N_awgn = 10;
berMatrix_EP_MSL = freqOffsetOFDMMSL(BPS,NS,M,SNR,ifftsize,carriers,N,ep,N_awgn);

% 固定频偏下，不同算法 误码率-信噪比曲线
figure
plot(SNR,  berMatrix_NOEP_Non,'-k' )
hold on
plot(SNR,  berMatrix_EP_Non ,'.-r')  
plot(SNR,  berMatrix_EP_ICI ,'--g')  
plot(SNR,  berMatrix_EP_SL ,'-m')  
plot(SNR,  berMatrix_EP_MSL ,'-c')  
set(gca,'YScale','log')

legend('未加频偏','无频偏估计','加频偏估计','SL','MSL');
grid on
xlabel( 'SNR(dB)')  
ylabel('BER')

nadi

HI,
I am looking for a matlab code to split OFDM sub-carriers into odd and even sub-carriers, can anyone help me please?

nadi