SNRdB = 0:5:30; num_runs = zeros(1,length(SNRdB));%发送次数 bernum_no_est = zeros(1,length(SNRdB));%错误比特数 ber_no_est = zeros(1,length(SNRdB));%误码率 blenum = zeros(1,length(SNRdB));%错误块数 bernum = zeros(1,length(SNRdB));%错误比特数 ber = zeros(1,length(SNRdB));%误码率 LS_est = zeros(length(pilot),Nofdm); % 导频信道 H_LS = zeros(Nfft,Nofdm); % 估计信道 H_mmse = zeros(Nfft,Nofdm); rsig_equal = zeros(Nfft,Nofdm); dsym = zeros(Nused,Nofdm); dsym_no_est = zeros(Nused,Nofdm); dmsg_no_est = zeros(Nused*log2(M),Nofdm); dmsg = zeros(Nused*log2(M),Nofdm); tic for ii = 1:length(SNRdB) for i_run = 1 : max_runs if mod(i_run, max_runs/resolution) == 1 disp(['Simualtion Running = ' num2str(i_run/max_runs)]) disp(['SNRdB = ' num2str(SNRdB(ii))]); disp(['blenum = ' num2str(blenum(ii))]); disp(['num_runs = ' num2str(num_runs(ii))]); disp(['ber = ' num2str(ber(ii))]); end什么意思？

这段代码是一个用于模拟无线通信系统的程序。它将会模拟在不同信噪比下的通信情况。具体来说，程序中的变量SNRdB是信噪比的取值范围，max_runs是每个信噪比下模拟的发送次数。程序将会统计每个信噪比下的误码率、错误比特数、错误块数等性能指标，并将其存储在对应的变量中。程序中还包含了信道估计和信道均衡的过程，以及用于数据传输的调制解调过程。最后，程序中的tic和toc函数用于计算程序的运行时间。

相关问题

clear all; bits_option =2; % 0:??????，1:??????，2：?????？ noise_option=1; % 0:??????，1:?????? b=4;NT=2; SNRdBs=[0:2:20];sq05=sqrt(0.5); nobe_target =500; BER_target =1e-3; raw_bit_len= 2592-6; nterleaving_num = 72; deinterleaving_num = 72;deinterleaving_num=72; N_frame = 1e8; for i_SNR=1:length(SNRdBs) sig_power=NT;SNRdB=SNRdBs(i_SNR); sigma2=sig_power*10^(-SNRdB/10)*noise_option;sigmal=sqrt(sigma2/2); nobe = 0; Viterbi_init for i_frame=1:1:N_frame 详细注释这段Matlab代码

这段Matlab代码是一个卷积码的性能评估程序，主要用于模拟不同信噪比下卷积码的误码率。下面是代码的详细注释：

% 清空所有变量
clear all; 

% 指定输入比特流的类型
bits_option =2; % 0:随机比特流，1:0比特流，2：1比特流

% 指定噪声类型
noise_option=1; % 0:AWGN，1:瑞利信道

% 码率和符号数
b=4;
NT=2;

% 指定信噪比的范围
SNRdBs=[0:2:20];

% 计算根号0.5
sq05=sqrt(0.5);

% 目标误码数和误码率
nobe_target =500; 
BER_target =1e-3; 

% 输入比特流长度
raw_bit_len= 2592-6; 

% 交织、反交织参数
nterleaving_num = 72; 
deinterleaving_num = 72;
deinterleaving_num=72; 

% 模拟帧数
N_frame = 1e8; 

% 循环计算不同信噪比下的误码率
for i_SNR=1:length(SNRdBs)
    sig_power=NT;
    SNRdB=SNRdBs(i_SNR);
    sigma2=sig_power*10^(-SNRdB/10)*noise_option;
    sigmal=sqrt(sigma2/2);
    nobe = 0; 
    Viterbi_init 
    for i_frame=1:1:N_frame 
        % 在这里对卷积码进行模拟，并统计误码率
        % ...
    end
end

其中，循环内的部分代码是主要的卷积码性能评估代码，用于模拟卷积码在不同信噪比下的误码率。具体的实现细节需要根据实际的卷积码来确定。

clear all; close all; clc; tic bits_options = [0,1,2]; noise_option = 1; b = 4; NT = 2; SNRdBs =[0:2:20]; sq05=sqrt(0.5); nobe_target = 500; BER_target = 1e-3; raw_bit_len = 2592-6; interleaving_num = 72; deinterleaving_num = 72; N_frame = 1e8; for i_bits=1:length(bits_options) bits_option=bits_options(i_bits); BER=zeros(size(SNRdBs)); for i_SNR=1:length(SNRdBs) sig_power=NT; SNRdB=SNRdBs(i_SNR); sigma2=sig_power10^(-SNRdB/10)noise_option; sigma1=sqrt(sigma2/2); nobe = 0; Viterbi_init for i_frame=1:1:N_frame switch (bits_option) case {0}, bits=zeros(1,raw_bit_len); case {1}, bits=ones(1,raw_bit_len); case {2}, bits=randi(1,raw_bit_len,[0,1]); end encoding_bits = convolution_encoder(bits); interleaved=[]; for i=1:interleaving_num interleaved=[interleaved encoding_bits([i:interleaving_num:end])]; end temp_bit =[]; for tx_time=1:648 tx_bits=interleaved(1:8); interleaved(1:8)=[]; QAM16_symbol = QAM16_mod(tx_bits, 2); x(1,1) = QAM16_symbol(1); x(2,1) = QAM16_symbol(2); if rem(tx_time-1,81)==0 H = sq05(randn(2,2)+jrandn(2,2)); end y = Hx; if noise_option==1 noise = sqrt(sigma2/2)(randn(2,1)+j*randn(2,1)); y = y + noise; end W = inv(H'H+sigma2diag(ones(1,2)))H'; X_tilde = Wy; X_hat = QAM16_slicer(X_tilde, 2); temp_bit = [temp_bit QAM16_demapper(X_hat, 2)]; end deinterleaved=[]; for i=1:deinterleaving_num deinterleaved=[deinterleaved temp_bit([i:deinterleaving_num:end])]; end received_bit=Viterbi_decode(deinterleaved); for EC_dummy=1:1:raw_bit_len, if bits(EC_dummy)~=received_bit(EC_dummy), nobe=nobe+1; end if nobe>=nobe_target, break; end end if (nobe>=nobe_target) break; end end = BER(i_SNR) = nobe/((i_frame-1)*raw_bit_len+EC_dummy); fprintf('bits_option:%d,SNR:%d dB,BER:%1.4f\n',bits_option,SNRdB,BER(i_SNR)); end figure; semilogy(SNRdBs,BER); xlabel('SNR(dB)'); ylabel('BER'); title(['Bits_option:',num2str(bits_option)]); grid on; end将这段代码改为有噪声的情况

以下是添加噪声后的修改代码：

clear all; close all; clc;
tic
bits_options = [0,1,2];
noise_option = 1;
b = 4;
NT = 2;
SNRdBs =[0:2:20];
sq05=sqrt(0.5);
nobe_target = 500;
BER_target = 1e-3;
raw_bit_len = 2592-6;
interleaving_num = 72;
deinterleaving_num = 72;
N_frame = 1e8;

for i_bits=1:length(bits_options)
bits_option=bits_options(i_bits);
BER=zeros(size(SNRdBs));

for i_SNR=1:length(SNRdBs)
sig_power=NT;
SNRdB=SNRdBs(i_SNR);
sigma2=sig_power*10^(-SNRdB/10)+noise_option;
sigma1=sqrt(sigma2/2);
nobe = 0;
Viterbi_init

for i_frame=1:1:N_frame
switch (bits_option)
case {0}, bits=zeros(1,raw_bit_len);
case {1}, bits=ones(1,raw_bit_len);
case {2}, bits=randi(1,raw_bit_len,[0,1]);
end
encoding_bits = convolution_encoder(bits);

interleaved=[];
for i=1:interleaving_num
interleaved=[interleaved encoding_bits([i:interleaving_num:end])];
end

temp_bit =[];
for tx_time=1:648
tx_bits=interleaved(1:8);
interleaved(1:8)=[];

QAM16_symbol = QAM16_mod(tx_bits, 2);

x(1,1) = QAM16_symbol(1);
x(2,1) = QAM16_symbol(2);

if rem(tx_time-1,81)==0
H = sq05*(randn(2,2)+j*randn(2,2));
end

y = H*x;

if noise_option==1
noise = sqrt(sigma2/2)*(randn(2,1)+j*randn(2,1));
y = y + noise;
end

W = inv(H'*H+sigma2*diag(ones(1,2)))*H';
X_tilde = W*y;

X_hat = QAM16_slicer(X_tilde, 2);

temp_bit = [temp_bit QAM16_demapper(X_hat, 2)];
end

deinterleaved=[];
for i=1:deinterleaving_num
deinterleaved=[deinterleaved temp_bit([i:deinterleaving_num:end])];
end

received_bit=Viterbi_decode(deinterleaved);

for EC_dummy=1:1:raw_bit_len,
if bits(EC_dummy)~=received_bit(EC_dummy),
nobe=nobe+1;
end
if nobe>=nobe_target,
break;
end
end

if (nobe>=nobe_target)
break;
end
end
BER(i_SNR) = nobe/((i_frame-1)*raw_bit_len+EC_dummy);
fprintf('bits_option:%d,SNR:%d dB,BER:%1.4f\n',bits_option,SNRdB,BER(i_SNR));
end
figure;
semilogy(SNRdBs,BER);
xlabel('SNR(dB)');
ylabel('BER');
title(['Bits_option:',num2str(bits_option)]);
grid on;
end