Matlab简单的OFDM仿真信道估计有BER曲线

《Matlab简单的OFDM仿真信道估计有BER曲线》由会员分享，可在线阅读，更多相关《Matlab简单的OFDM仿真信道估计有BER曲线（9页珍藏版）》请在装配图网上搜索。

1、clear all;close all;fprintf( n OFDM 仿真n n)% %参数定义% - %IFFT_bin_length = 1024;carrier_count= 200;bits_per_symbol = 2;symbols_per_carrier = 50;% 子载波数200% 位数/ 符号2% 符号数/ 载波50% 训练符号数10% 循环前缀长度T/4 （作者注明）All-zero CP% 调制方式QDPSK% 多径信道数2、3、4（缺省）% 信道最大时延7 （单位数据符号）% 仿真条件收发之间严格同步%SNR=input(SNR=);% 输入信噪比参数SNR=3:1

2、4;%定义信噪比范围BER=zeros(1,length(SNR);baseband_out_length =carrier_count *symbols_per_carrier *bits_per_symbol;% 计算发送的二进制序列长度carriers =(1: carrier_count) + (floor(IFFT_bin_length/4) -floor(carrier_count/2); % 坐标： (1 to 200) + 156 ,157 - 356conjugate_carriers=IFFT_bin_length-carriers+2; % 坐标 ：1024 - (157

3、:356) + 2 = 1026 - (157:356) = (869:670)% 构造共轭时间载波矩阵，以便应用所谓的 RCC，Reduced ComputationalComplexity算法，即ifft之后结果为实数% Define the conjugate time-carrier matrix%也可以用flipdim函数构造对称共轭矩阵% % 信 号 发 射% % %out = rand(1,baseband_out_length);%baseband_out1 = round(out) ;%baseband_out2 = floor(out*2) ;%baseband_out3

4、= ceil(out*2)-1 ;%baseband_out4 = randint(1,baseband_out_length);% 四种生成发送的二进制序列的方法，任取一种产生要发送的二进制序列%if (baseband_out1 = baseband_out2 & baseband_out1 = baseband_out3 )%fprintf(Transmission SequenceGenerated n n);%baseband_out = baseband_out1 ;%else%fprintf(Check Code n n);%end% 验证四种生成发送的二进制序列的方法baseb

5、and_out=round( rand(1,baseband_out_length);convert_matrix = reshape(baseband_out,bits_per_symbol,length(baseband_out)/bits_per_sy mbol);for k = 1length(baseband_out)/bits_per_symbol),modulo_baseband(k) = 0;for i = 1:bits_per_symbolmodulo_baseband(k) = modulo_baseband(k) + convert_matrix(i,k)*2(bits_

6、per_symbol - i);endend% 每2个比特转化为整数 0至3%采用lef t-msb方式%Test by lavabin%Abuilt-infunctionofdirectlychangebinarybitsintodecimalnumbers%convert_matrix1=zeros(length(baseband_out)/bits_per_symbol,bits_per_symbol);%convert_matrix1 = convert_matrix ;%Test_convert_matrix1=bi2de(convert_matrix1,bits_per_symbo

7、l,left-msb);%Test_convert_matrix2=bi2de(convert_matrix1,bits_per_symbol,right-msb);% 函数说明：% BI2DE Convert binary vectors to decimal numbers.% D = BI2DE(B) converts a binary vector B to a decimal value D. When B is% a matrix, the conversion is performed row-wise and the output D is a % column vector

8、of decimal values. The default orientation of thebinary % input is Right-MSB; the first element in B represents the least significant bit.%if (modulo_baseband = Test_convert_matrix1)% fprintf(modulo_baseband = Test_convert_matrix1 nnn);%else if (modulo_baseband = Test_convert_matrix2)%fprintf(modulo

9、_baseband = Test_convert_matrix2 nnn);%else%fprintf(modulo_baseband = any Test_convert_matrixnnn);%end%end% we get the result modulo_baseband = Test_convert_matrix1.% carrier_matrix reshape(modulo_baseband,carrier_count,symbols_per_carrier) % 生成时间载波矩阵% % QDPSK 调 制 % % carrier_matrix = zeros(1,carrie

10、r_count); carrier_matrix; % 添加一 个差分调制的初始相位，为0for i = 2symbols_per_carrier + 1)carrier_matrix(i, = rem(carrier_matrix(i, + carrier_matrix (i-1,2bits_per_symbol) ;% 差分调制endcarrier_matrix 二 carrier_matrix*(2*pi)/(2bits_per_symbol) ;% 产生差分相位X,Y=pol2cart(carrier_matrix,ones(size(carrier_matrix,1),size(ca

11、rrier_matrix,2); % 由极坐标向复 数坐标转化 第一参数为相位 第二参数为幅度% Carrier_matrix contains al l the phase informat ion and al l the ampl itudes are the plex_carrier_matrix = complex(X, Y) ;%添加训练序列training_symbols= 1j j 1-1 -j-j -1 1jj1-1-j-j-11jj1-1-j -j -11 j j1-1-j-j-11 j j1 -1 .-j -j -11 j j1-1-j-j-11 j j1 -1 -j-j

12、-11jj1-1-j-j-11j j 1 -1-j -j-1 1j j 1-1-j -j-1 .1 j j 1 -1-j-j-11 j j1 -1-j-j-1 1jj1-1-j-j-11jj1-1-j -j -1 1j j 1-1-j -j-1 1j j 1.-1 -j -j -1 1j j 1-1 -j-j -1 1j j 1 -1-j-j-11jj1-1-j-j-11 j j 1 -1-j-j-11 j j1 -1-j-j.-1 1 j j 1 -1 -j -j -1 1 j j 1 -1 -j -j -1 1 j j 1 -1 -j -j -1 1 j j 1-1 -j -j -1 ;

13、% 25 times 1 j j 1 , 25 times -1 -j -j -1, totally 200 symbols as a rowtraining_symbols = cat(1, training_symbols, training_symbols) ;training_symbols = cat(1, training_symbols, training_symbols) ;%Production of 4 rows of training_symbolscomplex_carrier_matrix=cat(1,training_symbols,complex_carrier_

14、matrix) ; % 训练序列与数据合并% block-type pilot symbolsIFFT_modulation = zeros(4 + symbols_per_carrier + 1,IFFT_bin_length)% Here a row vector of zeros is between training symbols and data symbols% 4 training symbols and 1 zero symbol% every OFDM symbol takes a row of IFFT_modulationIFFT_modulation(: , carr

15、iers) = complex_carrier_matrix; IFFT_modulation(: , conjugate_carriers) = conj(complex_carrier_matrix) % % Test by lavabin - Find the indices of zeros%index_of_zeros = zeros(symbols_per_carrier,IFFT_bin_length - 2*carrier_count);%IFFT_modulation1 = zeros(4 + symbols_per_carrier + 1,IFFT_bin_length);

16、 %IFFT_modulation2 = zeros(4 + symbols_per_carrier + 1,IFFT_bin_length); %IFFT_modulation1(6:symbols_per_carrier+5, = IFFT_modulation(6:symbols_per_carrier+5,=0 ;%for i = 1:symbols_per_carrier%index_of_zeros(i, = find(IFFT_modulation1(i+5,=1);%end% ti me_wave_ma trix = ifft(I FFT_modula ti on) ; % 进

17、行 IFFT 操作 time_wave_matrix=time_wave_matrix; %IfXisamatrix,ifftreturns the inverse Fourier transform of each column of the matrix.for i = 1: 4 + symbols_per_carrier + 1 windowed_time_wave_matrix(i,:)=real(time_wave_matrix(i,:);end% get the real part of the result of IFFT%这一步可以省略，因为IFFT结果都是实数%由此可以看出，

18、只是取了 IFFT之后载波上的点，并未进行CP的复制和添加 endofdm_modulation=reshape(windowed_time_wave_matrix,1,IFFT_bin_length*(4 + symbols_per_carrier + 1) ) ;% P2S operation%Test by lavabin%Another way of matrix transition%ofdm_modulation_tmp = windowed_time_wave_matrix.; %ofdm_modulation_test = ofdm_modulation_tmp(;%if (o

19、fdm_modulation_test = ofdm_modulation)% fprintf(ofdm_modulation_test = ofdm_modulation nnn);%else%fprintf(ofdm_modulation_test = ofdm_modulation nnn); %end% We get the result ofdm_modulation_test = ofdm_modulation . %Tx_data=ofdm_modulation;% % 信 道 模 拟% % d1=4;a1=0.2;d2=5;a2=0.3;d3=6;a3=0.4;d4=7;a4=

20、0.5; % 信道模拟copy1 = zeros(size(Tx_data) ;for i = 1 + d1: length(Tx_data) copy1(i) = a1*Tx_data( i - d1) ;endcopy2 = zeros(size(Tx_data) ) ;for i = 1 + d2: length( Tx_data) copy2(i) = a2*Tx_data( i - d2) ;end copy3 = zeros(size(Tx_data) ) ;for i = 1 + d3: length(Tx_data) copy3(i) = a3*Tx_data ( i - d3

21、) ;end copy4 = zeros(size(Tx_data) ) ;for i = 1 + d4: length( Tx_data) copy4(i) = a4*Tx_data(i - d4) ;endTx_data = Tx_data + copy1 + copy2 + copy3 + copy4; % 4 multi-paths Tx_signal_power = var(Tx_data);for idx=1:length(SNR)%monte carlo 仿真模拟linear_SNR = 10, SNR(idx) /IO);noise_sigma = Tx_signal_powe

22、r / linear_SNR; noise_scale_factor = sqrt(noise_sigma) ;noise = randn(1, length(Tx_data) )*noise_scale_factor; Rx_Data = Tx_data + noise;% % 信 号 接 收 % %Rx_Data_matrix = reshape(Rx_Data, IFFT_bin_length, 4+ symbols_per_carrier + 1)Rx_spectrum = fft(Rx_Data_matrix) ;% Suppose precise synchronazition b

23、etween Tx and Rx Rx_carriers = Rx_spectrum( carriers, : );Rx_training_symbols = Rx_carriers( (1: 4) , : ) ;Rx_carriers = Rx_carriers(5: 55), : ) ; % % 信 道 估 计% %Rx_training_symbols = Rx_training_symbols./ training_symbols;Rx_t raining_symbols_deno = Rx_t raining_symbols2;Rx_training_symbols_deno=Rx_

24、training_symbols_deno(1,+Rx_training_symbols_deno(2,+Rx_training_s ymbols_deno(3,+Rx_training_symbols_deno(4, ;Rx_training_symbols_nume = Rx_training_symbols(1, :)+Rx_training_symbols(2, :)+ Rx_training_symbols(3, :)+Rx_training_symbols(4, : ) ;Rx_training_symbols_nume = conj(Rx_training_symbols_num

25、e) ;% 取4个向量的导频符号是为了进行平均优化%都是针对“行向量”即单个的OFDM符号进行操作%原理：寻求1/H,对FFT之后的数据进行频域补偿% 1/H = conj(H)/2 because2 = H * conj(H)Rx_training_symbols=Rx_training_symbols_nume./Rx_training_symbols_deno;Rx_training_symbols=Rx_training_symbols_nume./Rx_training_symbols_deno;Rx_training_symbols_2=cat(1,Rx_training_symb

26、ols,Rx_training_symbols) ;Rx_training_symbols_4=cat(1,Rx_training_symbols_2,Rx_training_symbols_2)7Rx_training_symbols_8=cat(1,Rx_training_symbols_4,Rx_training_symbols_4)7Rx_training_symbols_16=Rx_training_symbols_8) ;cat(1,Rx_training_symbols_8,Rx_training_symbols_32=Rx_training_symbols_16) ;cat(1

27、,Rx_training_symbols_16,Rx_training_symbols_48=Rx_training_symbols_16) ;cat(1,Rx_training_symbols_32,Rx_training_symbols_50=Rx_training_symbols_2) ;cat(1,Rx_training_symbols_48,Rx_training_symbols=cat(1,Rx_training_symbols_50,Rx_training_symbols) ;Rx_carriers = Rx_training_symbols.*Rx_carriers; % 进行

28、频域单抽头均衡%Test of Using Rx_phase = angle(Rx_carriers)*(180/pi) phase_negative = find(Rx_phase 0) ;rem%Rx_phase1 = Rx_phase;%Rx_phase2 = Rx_phase;%Rx_phase1(phase_negative) = rem(Rx_phase1(phase_negative) + 360, 360) ; %Rx_phase2(phase_negative) = Rx_phase2(phase_negative) + 360 ;%if Rx_phase2(phase_ne

29、gative) = Rx_phase1(phase_negative)% fprintf(n There is no need using rem in negative phase transition.n) %else% fprintf(n We need to use rem in negative phase transition.n)%end%Rx_phase(phase_negative) = rem(Rx_phase(phase_negative) + 360, 360) ; % 把负的相位转化为正的相位Rx_decoded_phase = diff(Rx_phase) ;% 这

30、也是为什么要在前面加上初始相位的原因% “Here a row vector of ze ros is between training symbols and data symbols”phase_negative = find(Rx_decoded_phase 0) ;Rx_decoded_phase(phase_negative)= rem(Rx_decoded_phase(phase_negative) + 360, 360) ; % 再次把负的相位转化为正的相位% % QDPSK 解 调 % % base_phase = 360 /2bits_per_symbol; delta_ph

31、ase = base_phase /2;Rx_decoded_symbols=zeros(size(Rx_decoded_phase,1),size(Rx_decoded_phase,2) ;for i = 1: (2bits_per_symbol - 1)center_phase = base_phase*i;plus_delta = center_phase + delta_phase; % Decision threshold 1 minus_delta = center_phase - delta_phase; % Decision threshold 2 decoded=find(R

32、x_decoded_phase minus_delta) ;Rx_decoded_symbols(decoded) = i;end% 仅仅对三个区域进行判决% 剩下的区域就是零相位的空间了% 这个区域在定义解调矩阵时已经定义为零Rx_serial_symbols = reshape(Rx_decoded_symbols,1,size(Rx_decoded_symbols, 1)*size(Rx_decoded_symbols,2) ;for i = bits_per_symbol: -1: 1if i = 1Rx_binary_matrix(i, : ) = rem(Rx_serial_sym

33、bols, 2) ;Rx_serial_symbols = floor(Rx_serial_symbols/2) ; elseRx_binary_matrix( i, : ) = Rx_serial_symbols;endend% Integer to binarybaseband_in = reshape(Rx_binary_matrix, 1,size(Rx_binary_matrix, 1)*size(Rx_binary_matrix, 2) ) ;% % 误 码 率 计 算 % %bit_errors(idx) = find(baseband_in = baseband_out) ;%

34、 find的结果其每个元素为满足逻辑条件的输入向量的标号，其向量长度也就 是收发不一样的bit的个数%bit_error_count(idx) = size(bit_errors, 2) ; %total_bits = size( baseband_out, 2) ;%bit_error_rate = bit_error_count/ total_bits; %fprintf ( %f n,bit_error_rate) ;number_err(idx),BER(idx) = biterr(baseband_out,baseband_in ) ;endsemilogy(SNR,BER,r*);

35、legend(OFDM BER-SNR); xlabel(SNR (dB); ylabel(BER); title(OFDM);grid on;% % The END % % %1.该程序进行了简单的LMS信道估计，没有加入与MMSE等其他信道估计算法 的比较；%2.仿真条件为系统处于理想同步情况下。QjFile Edit View Insert Tools Desktop Window. Helpigure Zooiri lr： IOFDMTr10101010106SNR(dB)LU10 1 :-；= = = = = =匕=匕=；* OFDM BER-SNR10Matlab论坛iLoveMatlab,cn