matlab_OFDM通信系统的仿真。PDF文件，包括OFDM原理、程序讲解及运行结果

clear all; close all; fprintf('OFDM 仿真\n\n'); 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 % 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 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 -- 356 conjugate_carriers=IFFT_bin_length-carriers+2; % 坐标 ：1024 - (157:356) + 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 Computational Complexity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 baseband_out=round(rand(1,baseband_out_length)); convert_matrix =reshape(baseband_out,bits_per_symbol,length(baseband_out)/bits_per_symbol); for k=1:(length(baseband_out)/bits_per_symbol) modulo_baseband(k)=0; for i= 1:bits_per_symbol modulo_baseband(k)= modulo_baseband(k) +convert_matrix(i,k)*2^(bits_per_symbol-i); end end carrier_matrix=reshape(modulo_baseband,carrier_count,symbols_per_carrier); %QDPSK调制 carrier_matrix=[zeros(1,carrier_count);carrier_matrix]; for i=2:(symbols_per_carrier+1) carrier_matrix(i,:)=rem(carrier_matrix(i,:)+carrier_matrix(i-1,:),2^bits_per_symbol); end carrier_matrix = carrier_matrix *((2*pi)/(2^bits_per_symbol)); [X,Y]=pol2cart(carrier_matrix,ones(size(carrier_matrix,1),size(carrier_matrix,2))); complex_carrier_matrix=complex(X,Y); % 加训练序列 training_symbols=[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 -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 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 -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 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 -1 -j -j -1 1 j j 1 -1 -j -j -1 1 j j 1 -1 -j -j -1]; training_symbols=cat(1,training_symbols,training_symbols); training_symbols=cat(1,training_symbols,training_symbols); complex_carrier_matrix = cat(1,training_symbols,complex_carrier_matrix); IFFT_modulation=zeros(4 + symbols_per_carrier+ 1,IFFT_bin_length); IFFT_modulation(:,carriers)=complex_carrier_matrix; IFFT_modulation(:,conjugate_carriers)=conj(complex_carrier_matrix); time_wave_matrix=ifft(IFFT_modulation'); time_wave_matrix = time_wave_matrix'; for i= 1:4 + symbols_per_carrier + 1 windowed_time_wave_matrix(i,:) = real(time_wave_matrix(i,:)); end ofdm_modulation = reshape(windowed_time_wave_matrix',1,IFFT_bin_length*(4+symbols_per_carrier+1)); Tx_data = ofdm_modulation; d1 = 4; al = 0.2; d2 = 5; a2 = 0.3; d3 = 6; a3 = 0.4; d4 = 7; a4 = 0.5; copy1=zeros(size(Tx_data)); for i=1+d1:length(Tx_data) copy1(i)=a1*Tx_data(i-d1); end copy2=zeros(size(Tx_data)); for i= 1+d2:length(Tx_data) copy1(i)=a2*Tx_data(i-d2); end copy3=zeros(size(Tx_data)); for i= 1+d3:length(Tx_data) copy1(i)=a3*Tx_data(i-d3); end copy4=zeros(size(Tx_data)); for i=1+d4:length(Tx_data) copy1(i)=a4*Tx_data(i-d4); end Tx_data = Tx_data+copy1+copy2; Tx_signal_power=var(Tx_data); linear_SNR =10^(SNR/IO); noise_sigma = Tx_signal_power/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); 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_training_symbols_deno = Rx_training_symbols^2; Rx_training_symbols_deno =Rx_training_symbols_deno(1,:)+Rx_training_symbols_deno(2,:)+Rx_training_symbols_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_nume); Rx_trainmg_symbols = Rx_training_symbols_nume/Rx_traming_symbols_deno; Rx_trainmg_symbols_2 =cat(1,Rx_training_symbols,Rx_training_symbols); Rx_training_symbols_4 = cat(1,Rx_training_symbols_2,Rx_training_symbols_2); Rx_training_symbols_8 = cat(1,Rx_training_symbols_4,Rx_training_symbols_4); Rx_training_symbols_l6=cat(1,Rx_training_symbols_8,Rx_training_symbols_8); Rx_training_symbols_32=cat(1,Rx_training_symbols_16,Rx_training_symbols_16); Rx_training_symbols_48=cat(1,Rx_training_symbols_32,Rx_training_symbols_16); Rx_training_symbols_50=cat(1,Rx_training_symbols_48,Rx_training_symbols_2); Rx_training_symbols = cat(1,Rx_training_symbols_50,Rx_training_symbols); Rx_carriers = Rx_training_symbols*Rx_carriers; Rx_phase=angle(Rx_carriers)*(180/pi); phase_negative=find(Rx_phase<0); Rx_phase(phase_negative)=rem(Rx_phase(phase_negative)+360,360); Rx_decoded_phase= diff(Rx_phase); phase_negative=find(Rx_decoded_phase<0); Rx_decoded_phase(phase_negative)=rem(Rx_decoded_phase(phase_negative)+360,360); %QDPSK解调 base_phase =360/2^bits_per_symbol; delta_phase = base_phase/2; Rx_decoded_symbols = zeros(size(Rx_decoded_phase,1),size(Rx_decoded_phase,2)); for i= 1:(2^bits_per_symbol-1) center_phase = base_phase*i; plus_delta =center_phase+delta_phase; minus_delta = center_phase_delta_phase; decoded = find((Rx_decoded_phase <=plus_delta)&(Rx_decoded_phase>minus_delta)); Rx_decoded_symbols(decoded)=i; end Rx_serial_symbols = reshape(Rx_decoded_symbols,1,size(Rx_decoded_symbols,1)*size(Rx_decoded_symbols,2)); for i= bits_per_symbol:-1:1 if i~= 1 Rx_binary_matrix(i,:)=rem(Rx_serial_symbols,2); Rx_serial_symbols=floor(Rx_serial_symbols/2); else Rx_binary_matrix(i,:)=Rx_serial_symbols; end end baseband_in=reshape(Rx_binary_matrix,1,size(Rx_binary_matrix,1)*size(Rx_binary_matrix,2)); %误码率计算 bit_errors=find(baseband_in~=baseband_out); bit_error_count=size(bit_errors,2); total_bits=size(baseband_out,2); bit_error_rate = bit_error_count/total_bits; fprintf('%f\n',bit_eror_rate);