www.pudn.com > ofdm_simulation_primary.rar > ofdm_simulation_primary.m
clear all;
close all;
fprintf('OFDM仿真\n\n');
%fprintf：Write formatted(格式化的) data to file
IFFT_bin_length=1024;
carrier_count=200;
bits_per_symbol=2;
symbols_per_carrier=50;
SNR=input('SNR=');%输入SNR
baseband_out_length=carrier_count*symbols_per_carrier*bits_per_symbol;%baseband_out_length=20000
carriers=(1:carrier_count)+(floor(IFFT_bin_length/4)-floor(carrier_count/2));%1×200的数组，取值157~356
%floor：Round towards minus infinity，
% rounds the elements of A to the nearest integers less than or equal to A（四舍五入）
conjugate_carriers=IFFT_bin_length-carriers+2;%1×200的数组，取值869~670
%transmiting signal 信号发射
baseband_out=round(rand(1,baseband_out_length));%1×20000的数组，取值为0或1
%round：Round to nearest integer；rand：Uniformly distributed random numbers and arrays
convert_matrix=reshape(baseband_out,bits_per_symbol,length(baseband_out)/bits_per_symbol);%2×10000的数组，取值为0或1
%reshape：Reshape array
for k=1:(length(baseband_out)/bits_per_symbol)
%length：Length of vector
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);%1×10000的数组，取值为整数0~3
end
end
carrier_matrix=reshape(modulo_baseband,carrier_count,symbols_per_carrier)';%50×200的数组，取值为整数0~3
% QDPSK modulation QDPSK调制
carrier_matrix=[zeros(1,carrier_count);carrier_matrix];%51×200的数组，取值为整数0~3
%zeros：Create an array of all zeros
for i=2:(symbols_per_carrier+1)
carrier_matrix(i,:)=rem(carrier_matrix(i,:)+carrier_matrix(i-1,:),2^bits_per_symbol);
%rem:Remainder（余数） after division
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)));%X,Y都是51×200的数组
%pol2cart: Transform polar or cylindrical coordinates to Cartesian(将极坐标或柱坐标转化成笛卡儿坐标)
%ones: Create an array of all ones
%size：Array dimensions
complex_carrier_matrix=complex(X,Y);%51×200的复数数组
%complex：Construct complex data（复数） from real and imaginary components
%loading training symbols 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];%1×200的数组
training_symbols=cat(1,training_symbols,training_symbols);%2×200的数组
%cat：Concatenate（连接） arrays along specified dimension（维数）
training_symbols=cat(1,training_symbols,training_symbols);%4×200的数组
complex_carrier_matrix=cat(1,training_symbols,complex_carrier_matrix);%55×200的复数数组
IFFT_modulation=zeros(4+symbols_per_carrier+1,IFFT_bin_length);%55×1024的数组，取值全0
IFFT_modulation(:,carriers)=complex_carrier_matrix;%55×1024的数组，加载complex_carrier_matrix
IFFT_modulation(:,conjugate_carriers)=conj(complex_carrier_matrix);%55×1024的数组，加载complex_carrier_matrix的共轭
%conj：Complex conjugate（共轭）
time_wave_matrix=ifft(IFFT_modulation');%1024×55的矩阵，ifft的结果
%ifft：Inverse discrete（离散） Fourier transform
time_wave_matrix=time_wave_matrix';
for i=1:4+symbols_per_carrier+1
windowed_time_wave_matrix(i,:)=real(time_wave_matrix(i,:));%55×1024的数组
%real：Real part of complex number
end
ofdm_modulation=reshape(windowed_time_wave_matrix',1,IFFT_bin_length*(4+symbols_per_carrier+1));%1×56320的数组
Tx_data=ofdm_modulation;%1×56320的数组
%channel 信道
%多径传输
d1=4;a1=0.2;d2=5;a2=0.3;d3=6;a3=0.4;d4=7;a4=0.5;
copy1=zeros(size(Tx_data));%1×56320的数组
for i=1+d1:length(Tx_data)
copy1(i)=a1*Tx_data(i-d1);
end
copy2=zeros(size(Tx_data));%1×56320的数组
for i=1+d2:length(Tx_data)
copy1(i)=a2*Tx_data(i-d2);
end
copy3=zeros(size(Tx_data));%1×56320的数组
for i=1+d3:length(Tx_data)
copy1(i)=a3*Tx_data(i-d3);
end
copy4=zeros(size(Tx_data));%1×56320的数组
for i=1+d4:length(Tx_data)
copy1(i)=a4*Tx_data(i-d4);
end
Tx_data=Tx_data+copy1+copy2;%1×56320的数组
Tx_signal_power=var(Tx_data);%Tx_signal_power的值
%var:Variance(方差)
linear_SNR=10^(SNR /10);%linear_SNR的值
noise_sigma=Tx_signal_power/linear_SNR;%noise_sigma的值
noise_scale_factor=sqrt(noise_sigma);%noise_scale_factor的值
%sqrt：Square root
noise=randn(1,length(Tx_data))*noise_scale_factor;%1×56320的数组
%randn：Normally distributed random numbers and arrays
Rx_Data=Tx_data+noise;%1×56320的数组
%signal reception 信号接收
Rx_Data_matrix=reshape(Rx_Data,IFFT_bin_length,4+symbols_per_carrier+1);%1024×55的数组
Rx_spectrum=fft(Rx_Data_matrix);%1024×55的数组,fft的结果
%fft：Discrete Fourier transform
Rx_carriers=Rx_spectrum(carriers,:)';%55×200的数组
Rx_training_symbols=Rx_carriers((1:4),:);%4×200的数组
Rx_carriers=Rx_carriers((5:55),:);%51×200的数组
%signal estimate 信道估计（？有问题？）
Rx_training_symbols=Rx_training_symbols./training_symbols;%4×200的数组
Rx_training_symbols_deno=Rx_training_symbols.^2;%4×200的数组
Rx_training_symbols_deno=Rx_training_symbols_deno(1,:)+Rx_training_symbols_deno(2,:)+...
Rx_training_symbols_deno(3,:)+Rx_training_symbols_deno(4,:);%1×200的数组
Rx_training_symbols_nume=Rx_training_symbols(1,:)+Rx_training_symbols(2,:)+...
Rx_training_symbols(3,:)+Rx_training_symbols(4,:);%1×200的数组
Rx_training_symbols_nume=conj(Rx_training_symbols_nume);%1×200的数组,Rx_training_symbols_nume的共轭
Rx_training_symbols=Rx_training_symbols_nume./Rx_training_symbols_deno;%1×200的数组
Rx_training_symbols_2=cat(1,Rx_training_symbols,Rx_training_symbols);%2×200的数组
Rx_training_symbols_4=cat(1,Rx_training_symbols_2,Rx_training_symbols_2);%4×200的数组
Rx_training_symbols_8=cat(1,Rx_training_symbols_4,Rx_training_symbols_4);%8×200的数组
Rx_training_symbols_16=cat(1,Rx_training_symbols_8,Rx_training_symbols_8);%16×200的数组
Rx_training_symbols_32=cat(1,Rx_training_symbols_16,Rx_training_symbols_16);%32×200的数组
Rx_training_symbols_48=cat(1,Rx_training_symbols_32,Rx_training_symbols_16);%48×200的数组
Rx_training_symbols_50=cat(1,Rx_training_symbols_48,Rx_training_symbols_2);%50×200的数组
Rx_training_symbols=cat(1,Rx_training_symbols_50,Rx_training_symbols);%51×200的数组
Rx_carriers=Rx_training_symbols.*Rx_carriers;%51×200的数组
Rx_phase=angle(Rx_carriers)*(180/pi);%51×200的数组
%angle：Phase angle（相角）
phase_negative=find(Rx_phase<0);%phase_negative的数组
%find：Find indices（下标） and values of nonzero elements
Rx_phase(phase_negative)=rem(Rx_phase(phase_negative)+360,360);%51×200的数组
Rx_decoded_phase=diff(Rx_phase);%50×200的数组
%diff：Differences（差分） and approximate derivatives（导数）
phase_negative=find(Rx_decoded_phase<0);%phase_negative的数组
Rx_decoded_phase(phase_negative)=rem(Rx_decoded_phase(phase_negative)+360,360);%50×200的数组
% QDPSK demodulation QDPSK解调
base_phase=360/2^bits_per_symbol;%base_phase的值
delta_phase=base_phase/2;%delta_phase的值
Rx_decoded_symbols=zeros(size(Rx_decoded_phase,1),size(Rx_decoded_phase,2));%50×200的数组
for i=1:(2^bits_per_symbol-1)
center_phase=base_phase*i;%center_phase的值
plus_delta=center_phase+delta_phase;%plus_delta的值
minus_delta=center_phase-delta_phase;%minus_delta的值
decoded=find((Rx_decoded_phase<=plus_delta)&(Rx_decoded_phase>minus_delta));%decoded的数组
Rx_decoded_symbols(decoded)=i;%50×200的数组
end
Rx_serial_symbols=reshape(Rx_decoded_symbols',1,size(Rx_decoded_symbols,1)*...
size(Rx_decoded_symbols,2));%1×10000的数组
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);%1×10000的数组
else
Rx_binary_matrix(i,:)=Rx_serial_symbols;%2×10000的矩阵
end
end
baseband_in=reshape(Rx_binary_matrix,1,size(Rx_binary_matrix,1)*size(Rx_binary_matrix,2));%1×20000的数组
%BER calculation 误码率计算
bit_errors=find(baseband_in~=baseband_out);%bit_errors的数组
bit_error_count=size(bit_errors,2);%bit_error_count的值
total_bits=size(baseband_out,2);%total_bits的值
bit_error_rate=bit_error_count/total_bits;%bit_error_rate的值
fprintf('BER=%f\n',bit_error_rate);