求OFDM系统信道估计技术的MATLAB代码！

close all

clc

fprintf('OFDM信道估计仿真\n\n')

num_sc = 1200%-----------载波数目 2048简化为正蠢岩1200

num_symbol = 14 %--------------OFDM符号个数

data_symbol = [0,1,2,4,5,6,7,8,9,11,12,13]

pilot_symbol = [3,10]

cp_len = [160,144,144,144,144,144,144,160,144,144,144,144,144,144]

modulation_mode = 16%---------调制方式

q = 20

time_offset = 1 %us

time_offset = ceil(time_offset * 30.72) %20M bandwidth

SNR = 0:2:20%-------------信噪比取值

num_loop = 15%-----------------循环次数

num_ant = 2

num_bit_err=zeros(length(SNR),num_loop)

num_bit_err_dft=zeros(length(SNR),num_loop)

num_bit_err_ls=zeros(length(SNR),num_loop)

MSE=zeros(length(SNR),num_loop)

MSE1=zeros(length(SNR),num_loop)

MSE2=zeros(length(SNR),num_loop)

%%%%%%%%%%%%%%%%%%%%%%%Rx信号产生%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%---------------产生发送的随机序列举御————————————————————-

BitsLen = num_sc * length(data_symbol)

BitsTx = randint(1,BitsLen)

%---------------符号调制---------------------------------------—————

Modulated_Sequence=qammod(BitsTx,modulation_mode)

%---------------产生导档散频序列---------------------------------------———

prime_num = primes(num_sc)

prime_num = max(prime_num)

m = 0 : num_sc-1

xq = exp(-j*(pi*q*m.*(m+1)/prime_num))

pilot_symbols = xq( mod(m, prime_num) +1 )

pilot_symbols = pilot_symbols.'

%----------------导频插入-------------------------------------——————

piloted_ofdm_syms = zeros(num_sc, num_symbol)

piloted_ofdm_syms(:, data_symbol + 1) = reshape(Modulated_Sequence, num_sc, length(data_symbol))

piloted_ofdm_syms(:, pilot_symbol + 1) = repmat(pilot_symbols, 1, length(pilot_symbol))

%----------------IFFT变换—————————————————————————

time_signal = sqrt(num_sc) * ifft(piloted_ofdm_syms)

%----------------加循环前缀------------------------------------—————

Tx_data_trans = []

for k = 1 : num_symbol

add_cyclic_signal = [time_signal(num_sc - cp_len(k)+1 : num_sc, k)time_signal(:, k)].'

Tx_data_trans = [Tx_data_trans,add_cyclic_signal]

end

%%%%%%%%%%%%%%%%%%%%%%%主程序循环%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

for c1 = 1:length(SNR)

fprintf('\n\n\n仿真信噪比为%f\n\n',SNR(c1))

for num1 = 1:num_loop

%----------------信道处理--------------------------------------

%ADD awgn

Tx_signal_power = sum(abs(Tx_data_trans(:)).^2) / length(Tx_data_trans(:))

noise_var = Tx_signal_power/(10^(SNR(c1)/10))

Rx_data(1, :) = awgn(Tx_data_trans, SNR(c1), 'measured')

Rx_data(2, :) = awgn(Tx_data_trans, SNR(c1), 'measured')

%ADD TO 正时偏

Rx_data(1, :) = [zeros(1,time_offset),Rx_data(1, 1:length(Tx_data_trans)-time_offset),]

Rx_data(2, :) = [zeros(1,time_offset),Rx_data(2, 1:length(Tx_data_trans)-time_offset),]

% %ADD TO 负时偏

% Rx_data(1, :) = [Rx_data(1, time_offset+1:length(Tx_data_trans)),zeros(1,time_offset)]

% Rx_data(2, :) = [Rx_data(2, time_offset+1:length(Tx_data_trans)),zeros(1,time_offset)]

%----------------信号接收、去循环前缀、FFT变换-----------------

%Ant0

total_len=0

for k=1 : num_symbol

Rx_signal_matrix(:, k) = Rx_data(1, total_len+cp_len(k)+1 : total_len+cp_len(k)+num_sc).'

total_len = total_len+cp_len(k)+num_sc

end

Rx_carriers_ant0 = fft(Rx_signal_matrix)/sqrt(num_sc)

%Ant1

total_len=0

for k=1 : num_symbol

Rx_signal_matrix(:, k) = Rx_data(2, total_len+cp_len(k)+1 : total_len+cp_len(k)+num_sc).'

total_len = total_len+cp_len(k)+num_sc

end

Rx_carriers_ant1 = fft(Rx_signal_matrix)/sqrt(num_sc)

%----------------导频和数据提取--------------------------------

Rx_pilot_ant0 = Rx_carriers_ant0(:, pilot_symbol+1)

Rx_data_ant0 = Rx_carriers_ant0(:, data_symbol+1)

Rx_pilot_ant1 = Rx_carriers_ant1(:, pilot_symbol+1)

Rx_data_ant1 = Rx_carriers_ant1(:, data_symbol+1)

%----------------导频位置LS信道估计------------------------———

pilot_patt = repmat(pilot_symbols, 1, length(pilot_symbol))

pilot_esti_ant0 = Rx_pilot_ant0.*conj(pilot_patt)

pilot_esti_ant1 = Rx_pilot_ant1.*conj(pilot_patt)

%----------------LS估计的信道系数平铺———————————————

LS_channel_coeff_ant0 = [repmat(pilot_esti_ant0(:, 1), 1, length(data_symbol)/2), ...

repmat(pilot_esti_ant0(:, 2), 1, length(data_symbol)/2)]

LS_channel_coeff_ant1 = [repmat(pilot_esti_ant1(:, 1), 1, length(data_symbol)/2), ...

repmat(pilot_esti_ant1(:, 2), 1, length(data_symbol)/2)]

%----------------导频位置DFT信道估计----------------------------

Tx_pilot_estimate_ifft_ant0 = ifft(pilot_esti_ant0)

Tx_pilot_estimate_ifft_ant1 = ifft(pilot_esti_ant1)

stem(1:1200, Tx_pilot_estimate_ifft_ant0(:,1))

grid on

h_len = cp_len(2)

Tx_pilot_estimate_ifft_ant0(h_len+1 : num_sc-h_len, :) = 0

Tx_pilot_estimate_dft_ant0 = fft(Tx_pilot_estimate_ifft_ant0)

Tx_pilot_estimate_ifft_ant1(h_len+1 : num_sc-h_len, :) = 0

Tx_pilot_estimate_dft_ant1 = fft(Tx_pilot_estimate_ifft_ant1)

%----------------DFT估计的信道系数平铺———————————————

DFT_channel_coeff_ant0 = [repmat(Tx_pilot_estimate_dft_ant0(:, 1), 1, length(data_symbol)/2),...

repmat(Tx_pilot_estimate_dft_ant0(:, 2), 1, length(data_symbol)/2)]

DFT_channel_coeff_ant1 = [repmat(Tx_pilot_estimate_dft_ant1(:, 1), 1, length(data_symbol)/2),...

repmat(Tx_pilot_estimate_dft_ant1(:, 2), 1, length(data_symbol)/2)]

%----------------ZF OR MRC EQ----------------------

Tx_data_estimate_dft = (Rx_data_ant0.*conj(DFT_channel_coeff_ant0) + Rx_data_ant1.*conj(DFT_channel_coeff_ant1))...

./((abs(DFT_channel_coeff_ant0).^2) + (abs(DFT_channel_coeff_ant0).^2))

Tx_data_estimate_ls = (Rx_data_ant0.*conj(LS_channel_coeff_ant0) + Rx_data_ant1.*conj(LS_channel_coeff_ant1))...

./((abs(LS_channel_coeff_ant0).^2) + (abs(LS_channel_coeff_ant1).^2))

%----------------DFT符号解调------------------------------------

demod_in_dft=Tx_data_estimate_dft(:).'

demod_out_dft=qamdemod(demod_in_dft,modulation_mode)

%----------------LS符号解调------------------------------------

demod_in_ls=Tx_data_estimate_ls(:).'

demod_out_ls=qamdemod(demod_in_ls,modulation_mode)

%----------------误码率的计算-----------------------------------

for i=1:length(BitsTx)

if demod_out_dft(i)~=BitsTx(i)

num_bit_err_dft(c1,num1)=num_bit_err_dft(c1,num1)+1

end

if demod_out_ls(i)~=BitsTx(i)

num_bit_err_ls(c1,num1)=num_bit_err_ls(c1,num1)+1

end

end

end

end

BER_dft=mean(num_bit_err_dft.')/length(BitsTx)

BER_ls=mean(num_bit_err_ls.')/length(BitsTx)

%%%%%%%%%%%%%%%%%%%a%%%%%%%%主程序循环换结束%%%%%%%%%%%%%%%%%%%%%%%%%%%%

figure

semilogy(SNR,BER_dft,'-mp',SNR,BER_ls,'-k+')

xlabel('SNR')

ylabel('BER')

legend('DFT信道估计','LS信道估计')

title('OFDM系统的LS和DFT信道估计')

grid on

%本程序用于OFDM基本原理仿真

%数据调制采用QPSK

clear allclc

%*****************参数设置部分**********************

SNR=10 %信噪比取值，dB为单位

fl=128 %设置FFT长度

Ns=6 %设置一个帧结构中OFDM信号的个数

para=128%设置并行传输的子载波个数

gl=32 %设置保护时隙的长度

%***************发送端部分*************************

Signal=rand(1,para*Ns*2)>0.5 %产生0,1随机数列，符号个数为para*2*Ns

%for i=1:para

%for j=1:Ns*2

% SigPara(i,j)=Signal(i*j)错误的，作野雹者是傻X

%串并转换，将随机产生的二进制矩阵变换为行数为para，列谨贺数为2*Ns的矩阵

%end

%end

SigPara=reshape(Signal,para,2*Ns)

%***********进行QPSK数据调制，将数据分为两个通道**************

for j=1:Ns

ich(:,j)=SigPara(:,2*j-1)

qch(:,j)=SigPara(:,2*j)

end

kmod=1./sqrt(2)

ich1=ich.*kmod

qch1=qch.*kmod

x=ich1+qch1.*sqrt(-1) %产生复信号

y=ifft(x) %通过傅里叶反变换，将频域数据转换为时域数据

ich2=real(y)%I信道取变换后的实部

qch2=imag(y) %I信道取变换后的虚部

%*******************插入保护间祥脊派隔*******************

ich3=[ich2(fl-gl+1:fl,:)ich2]

qch3=[qch2(fl-gl+1:fl,:)qch2]

%******************并串转换*********************

ich4=reshape(ich3,1,(fl+gl)*Ns)

qch4=reshape(qch3,1,(fl+gl)*Ns)

%*****************形成复数发射数据***************

TrData=ich4+qch4.*sqrt(-1)

ReData=awgn(TrData,SNR,'measured')

%接收端 移去保护时隙

idata=real(ReData)

qdata=imag(ReData)

idata1=reshape(idata,fl+gl,Ns)

qdata1=reshape(qdata,fl+gl,Ns)

idata2=idata1(gl+1:gl+fl,:)

qdata2=qdata1(gl+1:gl+fl,:)

%********FFT*****************

Rex=idata2+qdata2*sqrt(-1)

ry=fft(Rex)

ReIchan=real(ry)

ReQchan=imag(ry)

ReIchan=ReIchan/kmod

ReQchan=ReQchan/kmod

%*******QPSK逆映射*********

for j=1:Ns

RePara(:,2*j-1)=ReIchan(:,j)

RePara(:,2*j)=ReQchan(:,j)

end

ReSig=reshape(RePara,1,para*Ns*2)

%符号抽样判决

ReSig=ReSig>0.5

figure

subplot(2,1,1)

stem(ReSig(1:1000))

legend('输出数据')

grid

subplot(2,1,2)

stem(Signal(1:1000))

legend('输入数据')

grid

%end of script file