clear all; %% 参数设置 M = 4; % 调制阶数 N = 1e5; % 仿真比特数 SNRdB = 0:1:14; % 信噪比范围 Es = 1; % 符号能量 Eb = Es / log2(M); % 比特能量 sigma = sqrt(Es ./ (2 * 10 .^ (SNRdB/10))); % 噪声标准差 %% 信源产生信息比特 bits = randi([0, 1], 1, N); %% 调制 symbols = zeros(1, N/2); for i = 1:N/2 if bits(2i-1)==0 && bits(2i)==0 symbols(i) = -3; elseif bits(2i-1)==0 && bits(2i)==1 symbols(i) = -1; elseif bits(2i-1)==1 && bits(2i)==0 symbols(i) = 1; elseif bits(2i-1)==1 && bits(2i)==1 symbols(i) = 3; end end %% 信道 noises = randn(1, N/2) .* sigma; received = symbols + noises; %% 接收端检测 LLR = zeros(1, N); for i = 1:N/2 LLR(2i-1) = received(i) / sigma(find(SNRdB==SNRdB(i))); LLR(2i) = LLR(2i-1); end %% 将检测结果与信源原始信息比较计算误符号率和误比特率 BER = zeros(size(SNRdB)); SER = zeros(size(SNRdB)); for i = 1:length(SNRdB) % 接收端检测 noises = randn(1, N/2) . sigma(i); received = symbols + noises; LLR = zeros(1, N); for j = 1:N/2 LLR(2j-1) = received(j) / sigma(i); LLR(2j) = LLR(2j-1); end % 软判决译码 bits_hat = zeros(1, N); for j=1:N/2 if LLR(2j-1)>0 bits_hat(2j-1) = 1; end if LLR(2j)>0 bits_hat(2j) = 1; end end % 统计误码率 BER(i) = sum(bits~=bits_hat) / N; SER(i) = sum(symbols~=received) / (N/2); end %% 作图 semilogy(SNRdB, SER, 'k-o', 'linewidth', 2); hold on; semilogy(SNRdB, qfunc(sqrt(210.^(SNRdB/10))), 'r', 'linewidth', 2); grid on; xlabel('SNR(dB)'); ylabel('Symbol Error Rate'); legend('Simulation', 'Theory'); 这个程序出现了错误使用 .* 矩阵维度必须一致。出错 Untitled (第 29 行) noises = randn(1, N/2) .* sigma; 错误，请更改形成新的MATLAB程序

MATLAB仿真BPSK调制-综合文档

6. 误码率计算：统计错误解调的比特数，除以总比特数，得到误码率（BER）。 7. 可视化：绘制星座图、眼图等，帮助分析调制性能。三、MATLAB代码实现以下是一个简单的BPSK调制仿真MATLAB代码框架： matlab %...

基于Matlab的2DPSK调制解调系统仿真.zip

在本文中，我们将深入探讨基于Matlab的2DPSK（二维相移键控）调制解调系统仿真。2DPSK是一种扩展了传统PSK（相移键控）概念的多维调制技术，它通过在两个正交分量上改变载波相位来传输信息。Matlab作为强大的数值...

clc; clear;%% 1. 信源 bits = randi([0,1],1,1000); % 生成随机的比特序列%% 2. 扩频% 生成Walsh函数 N = 8; walshMat = hadamard(N); walshSeq = walshMat(1,:);% 生成扩频码 spreadCode = repmat(walshSeq,1,length(bits)/N);% 扩频 spreadBits = bits.spreadCode;%% 3. 信道% 添加高斯白噪声 SNRdB = 0:2:16; SNR = 10.^(SNRdB/10); for i = 1:length(SNR) noiseVar = 1/SNR(i); noise = sqrt(noiseVar)randn(1,length(spreadBits)); channelOut = spreadBits + noise; %% 4. 解扩 % 解扩 despreadBits = channelOut./spreadCode; despreadBits(isnan(despreadBits)) = 0; %% 5. 信宿 % BPSK调制 modSignal = 1-2despreadBits; % 接收滤波器 b = ones(1,N); a = 1; rxSignal = filter(b,a,modSignal); %% 6. BER-SNR曲线 % 计算误码率 err = sum(rxSignal<0) + sum(rxSignal>0); % 统计错误比特数 ber(i) = err/length(bits); % 计算误码率 % 绘制BER-SNR曲线 semilogy(SNRdB,ber,'-'); xlabel('SNR(dB)'); ylabel('BER'); title('BER-SNR曲线'); grid on; hold on; ,优化代码

以下是优化后的代码： ... % 统计错误比特数 ber(i) = err/length(bits); % 计算误码率 end % 绘制BER-SNR曲线 semilogy(SNRdB,ber,'-*'); xlabel('SNR(dB)'); ylabel('BER'); title('BER-SNR曲线'); grid on;

clear, clf %%%************** 参数设置 Nfft=128; % FFT size Nbps=2; M=2^Nbps; % Number of bits per (modulated) symbol Es=1; A=sqrt(3/2/(M-1)*Es); % Signal energy and QAM normalization factor N=Nfft; Ng=Nfft/4; %CP长度 Nofdm=Nfft+Ng; %OFDM符号长度+CP长度 Nsym=3; x=[]; Nps = 8; %梳状导频中非零值间隔 %%%%****频偏设置 CFO = 3.75; % CFO = 0; for m=1:Nsym msgint=randi([0 M-1],1,N); %bits_generator(1,NsymN,Nbps) if m<=2 Xp = add_pilot(zeros(1,Nfft),Nfft,Nps); Xf=Xp; % add_pilot Xf_temp = Xp; %后续会用到用于算整数倍频偏 else Xf = A.qammod(msgint,M,'UnitAveragePower',true); end xt = ifft(Xf,Nfft); x_sym = add_CP(xt,Ng); x= [x x_sym]; end %*********** 信道 %channel 可添加所需信道 y=x; % No channel effect %信号功率计算 sig_pow= yy'/length(y); % Signal power calculation %%%%%%%%SNRdB设置 SNRdBs= 0:3:30; MaxIter = 1000; MSE_train = zeros(1,length(SNRdBs)); for i=1:length(SNRdBs) SNRdB = SNRdBs(i); MSE_CFO_CP = 0; MSE_CFO_train = 0; y_CFO= add_CFO(y,CFO,Nfft); % Add CFO %%%%多次迭代取平均 for iter=1:MaxIter %y_aw=add_AWGN(y_CFO,sig_pow,SNRdB,'SNR',Nbps); % AWGN added, signal power=1 y_aw = awgn(y_CFO,SNRdB,'measured'); % AWGN added, signal power=1 %%%%% 估计出来的频偏只能在[-0.5D,0.5D]，也即[-0.5Nps,0.5*Nps] Est_CFO_train = CFO_train_sim1(y_aw,Nfft,Nps); MSE_CFO_train = MSE_CFO_train + (Est_CFO_train-CFO)^2; end % the end of for (iter) loop MSE_train(i) = MSE_CFO_train/MaxIter; end%ebn0 end semilogy(SNRdBs, MSE_train,'-x'); xlabel('SNR[dB]'); ylabel('MSE'); title('CFO Estimation'); legend('时域训练序列')这段代码的实现过程

1. 设置参数，包括FFT大小、调制方式、信号能量、循环前缀长度等。 2. 生成随机调制信号，并添加梳状导频，其中前两个OFDM符号使用全0梳状导频。 3. 对每个OFDM符号进行IFFT变换和添加循环前缀。 4. 将所有OFDM...

clear all; close all; clc;tic 5%8866% Settings $8868% its_option =2; 966 0:??????，1:??????，2：?????？ hoise_option=1; 8% 0:??????，1:?????? =4;NT=2; SNRdBs=[0:2:20];sq05=sqrt(0.5); obe_target =500; BER_target =1e-3; taw_bit_len= 2592-6; nterleaving_num = 72; deinterleaving_num = 72; _frame = 1e8; or i_SNR=1:length(SNRdBs) sig_power=NI;SNRdB=SNRdBs(i_SNR); sigma2=sig_power10°(-SNRdB/10)noise_option;sigmal=sqrt(sigma2/2); nobe = 0; Viterbi_init for i_frame=1:1:N_frame I %%88688868896%% ??????866988689686836% switch (bits_option) case (0】, bits=zeros(1,raw_bit_len); case (11, bits=ones(1,raw_bit_len); casef2), bits=randint(1,raw_bit_len); case (2), bits=randi(1,1,raw_bit_len)-1; end 686%6% ?????88%6% encoding_bits= convolution_encoder(bits); 6%%8%% ????? 8686% interleaved=[]; for i=l:interleaving_mum interleaved=[interleavedencoding_bits([i:interleaving_mum:end])];for tx_time-l:648 tx_bits=interleaved(1:8); interleaved(1:8)=[J; ??7 QAM16_symbol=QAM16_mod(tx_bits, 2); ?????69686666366685669 x(1,1) =QAM16_symbol(1);x(2,h)=QAM16_symbol(2); 90969696%????????????? 636585863666666 if rem(tx_time-1,81)==0 H = sq05(randn(2,2)+jrandn(2,2)); end y =Hx; 66986896%88868% ????? 6688688%%88%% noise = sqrt(sigma2/2)(randn(2,1)+jrandn(2,1)); if noise_option==1, y = y + noise;end %8%8%88%%8%8% ??????668888688888%% W=inv(H'H+sigma2diag (ones(1,2)))H'; K_tilde =Wy; %%%%88%%8%8% ??????668888%58888%% x_hat = QAM16_slicer(X_tilde, 2); temp_bit=[temp_bit QAM16_denapper(X_hat, 2)]; end %%%8%%%%?????88%8886% deinterleaved=[]; for i=1:deinterleaving_rum deinterleaved=[deinterleaved temp_bit([i:deinterleaving_mum:end])];end %%%86%%%?22220%%%866% received_bit=Viterbi_decode(deinterleaved) 600%%22222 5%0%% for EC_dummy=1:1:raw_bit_len, A bit(BC dumnv) nahesnobe+1:endif nobe>=nobe_target, break; end end if (nobe>=nobe_target) break; end end %8%888888%%%%save BER data & Display 8%88%8888%88%BER(i_SNR)=nobe/((i_frame-1)raw_bit_len+EC_dummy);fprintf(’t%dt\t%1.4f\n', SNRdB,BER(i_SNR)); if BER(i_SMR)<BER_target, break; end end详细注释这段matlab代码

首先设置了一些参数，包括使用的编码方式、噪声选项、帧数、信噪比等。然后进入一个主循环，循环中对于每一帧数据，进行编码、交织、调制、信道传输、解调、反交织、译码等操作，并计算误比特率（BER）。如果达到...

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(Nusedlog2(M),Nofdm); dmsg = zeros(Nusedlog2(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？

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...

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_power10^(-SNRdB/10)noise_option;sigmal=sqrt(sigma2/2); nobe = 0; Viterbi_init for i_frame=1:1:N_frame 注释这段Matlab代码

程序中还定义了一些其他参数，如 raw_bit_len、nterleaving_num、deinterleaving_num、N_frame 等，用于控制交织、反交织等操作。在程序的主要循环中，根据不同的信噪比对卷积码进行模拟，并统计误码率。

请解释一下如下代码b=1; % 系统参数b固定 min_a=0; % 参数a最小 div_a=0.01; % 参数a迭代步长 max_a=1; % 参数a最大 M=(max_a-min_a)/div_a+1; % 参数a迭代次数 alp=1.8; snrdb=50; snr=10^(snrdb/10); load EPSI1; sig1=EPSI1(12800+1:12800+1280); % 取第101至110个周期的EP信号 NN=1000; % 重采样率 s1=interp(sig1(1:1283),NN); N=length(s1); % 随机微分方程数值解的点数 tt=1/NN; % 随机微分方程数值解的时间步长 MM=2; % 独立运行的次数 mm=1; d=zeros(MM,1); a_est=zeros(MM,1); for index=1:MM % v0=randn(N,1); gamma=1; p=alp; v1=(alpha(N,alp,0,gamma,0))'; s1=gammasqrt(snr)s1/std(s1); % 用噪声强度（分散系数为1）和信噪比来确定信号大小 x1=s1+v1; % x1=atan(x1); % x1=abs(x1).^(alp-1).sign(x1); %---algorithm--- y1=zeros(N,M); xx1=zeros(N/NN,1); yy1=zeros(N/NN,M); c_coe1=zeros(M,1); m=1; for a=min_a:div_a:max_a; y1(1,1)=1; for n=1:N-1 y1(n+1,m)=y1(n,m)+tt(ay1(n,m)-by1(n,m)^3+x1(n)); end xx1=downsample(x1,NN); yy1(:,m)=downsample(y1(:,m),NN); ss1=downsample(s1,NN); xx1_yy1(m)=(1/length(xx1))sum(xx1.(abs(yy1(:,m)).^(p-1).sign(yy1(:,m)))); % 计算输入输出的对称共变系数c_cor yy1_xx1(m)=(1/length(yy1(:,m)))sum(yy1(:,m).(abs(xx1).^(p-1).sign(xx1))); xx1_xx1(m)=(1/length(xx1))sum(xx1.(abs(xx1).^(p-1).sign(xx1))); yy1_yy1(m)=(1/length(yy1(:,m)))sum(yy1(:,m).(abs(yy1(:,m)).^(p-1).sign(yy1(:,m)))); c_coe1(m)=(xx1_yy1(m)yy1_xx1(m))/(xx1_xx1(m)yy1_yy1(m)); % 对称共变系数 m=m+1; end [val1,loc1]=max(c_coe1);% 确定最佳a值a_est、 a_est(mm)=(loc1-1)div_a+min_a; cc_ss1yy1=xcov(ss1,abs(yy1(:,loc1)).^(p-1).sign(yy1(:,loc1))); % 了解随机共振系统的延时d，应该a相同时看延时是否相同 [val,loc]=max(cc_ss1yy1); d(mm)=length(ss1)-loc; mm=mm+1; end a_est d dd=mean(d) figure(1) % 观察最佳a值a_est时的输入xx1、输出yy1(:,loc1) subplot(411),plot(ss1) subplot(412),plot(xx1) loc=(a_est(mm-1)-min_a)/div_a+1 % 众数? subplot(413),plot(yy1(:,loc)) a=min_a:div_a:max_a; subplot(414),plot(a,c_coe1,'')

2. 根据参数a的最小值、最大值和迭代步长计算参数a的迭代次数M。 3. 定义信噪比和信号sig1，并对信号进行重采样。 4. 定义独立运行次数MM和存储结果的数组d和a_est。 5. 对于每次独立运行，计算随机微分方程的...

clear all; close all; clc;ticits_option = 2;noise_option = 1;raw_bit_len = 2592-6;interleaving_num = 72;deinterleaving_num = 72;N_frame = 1e4;SNRdBs = [0:2:20];sq05 = sqrt(0.5);bits_options = [0, 1, 2]; % 三种bits-option情况obe_target = 500;BER_target = 1e-3;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 = 1; SNRdB = SNRdBs(i_SNR); sigma2 = sig_power * 10^(-SNRdB/10); sigma = sqrt(sigma2/2); nobe = 0; for i_frame = 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([0,1], 1, raw_bit_len); 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 = sigma * (randn(2,1) + j * randn(2,1)); y = y + noise; end W = inv(H' * H + sigma2 * diag(ones(1,2))) * H'; K_tilde = W * y; x_hat = QAM16_slicer(K_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 nobe >= obe_target break; end if received_bit(EC_dummy) ~= bits(EC_dummy) nobe = nobe + 1; end end if nobe >= obe_target break; end end BER(i_SNR) = nobe / (i_frame * raw_bit_len); 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注释这段matlab代码

N_frame = 1e4; % 帧数 SNRdBs = [0:2:20]; % 信噪比范围 sq05 = sqrt(0.5); % sqrt(0.5)的值 bits_options = [0, 1, 2]; % 三种bits-option情况 obe_target = 500; % 最大误比特数目 BER_target = 1e-3; % 误...

clear all; close all; clc;tic its_option =2; hoise_option=1; =4;NT=2; SNRdBs=[0:2:20];sq05=sqrt(0.5); obe_target =500; BER_target =1e-3; taw_bit_len= 2592-6; nterleaving_num = 72; deinterleaving_num = 72; _frame = 1e8; or i_SNR=1:length(SNRdBs) sig_power=NI;SNRdB=SNRdBs(i_SNR); sigma2=sig_power10°(-SNRdB/10)noise_option;sigmal=sqrt(sigma2/2); nobe = 0; Viterbi_init for i_frame=1:1:N_frame I switch (bits_option) case (0】, bits=zeros(1,raw_bit_len); case (11, bits=ones(1,raw_bit_len); casef2), bits=randint(1,raw_bit_len); case (2), bits=randi(1,1,raw_bit_len)-1; end encoding_bits= convolution_encoder(bits);interleaved=[]; for i=l:interleaving_mum interleaved=[interleavedencoding_bits([i:interleaving_mum:end])];解释一下上述代码中构造sq05的原因

由于标准差为1的正态分布随机变量的方差为1，因此其均方根值也为1。而由于sq05=sqrt(0.5)，因此sq05的平方等于0.5，即标准差为1的正态分布随机变量的方差为0.5，因此在使用sq05作为系数时，需要将接收信号乘以sqrt(2...

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)+jrandn(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

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 =...

请帮我对下面的代码添加注释：copyfile('commlteMIMO_params_QAM16.m','commlteMIMO_params.m'); commlteMIMO_params; [prmLTEPDSCH, prmLTEDLSCH, prmMdl] = commlteMIMO_initialize(txMode, ... chanBW, contReg, modType, Eqmode,numTx, numRx,cRate,maxIter, fullDecode, chanMdl, corrLvl, ... chEstOn, numCodeWords, enPMIfback, cbIdx, snrdB, maxNumErrs, maxNumBits); clear txMode chanBW contReg modType Eqmode numTx numRx cRate maxIter fullDecode chanMdl corrLvl chEstOn numCodeWords enPMIfback cbIdx snrdB maxNumErrs maxNumBits %% disp('Simulating the LTE Mode 4: Multiple Tx & Rx antrennas with Spatial Multiplexing'); zReport_data_rate(prmLTEPDSCH, prmLTEDLSCH); hPBer = comm.ErrorRate; snrdB=prmMdl.snrdB; maxNumErrs=prmMdl.maxNumErrs; maxNumBits=prmMdl.maxNumBits; %% Simulation loop tic; nS = 0; % Slot number, one of [0:2:18] Measures = zeros(3,1); %initialize BER output while (( Measures(2)< maxNumErrs) && (Measures(3) < maxNumBits)) [dataIn, dataOut, txSig, rxSig, dataRx, yRec, csr] = ... commlteMIMO_SM2_step(nS, snrdB, prmLTEDLSCH, prmLTEPDSCH, prmMdl); % Calculate bit errors Measures = step(hPBer, dataIn, dataOut); % Visualize constellations and spectrum if (visualsOn && prmLTEPDSCH.Eqmode~=3) zVisualize( prmLTEPDSCH, txSig, rxSig, yRec, dataRx, csr, nS); end; % Update subframe number nS = nS + 2; if nS > 19, nS = mod(nS, 20); end; end disp(Measures); toc;

% 从模型参数中获取信噪比和最大误码数、比特数 snrdB=prmMdl.snrdB; maxNumErrs=prmMdl.maxNumErrs; maxNumBits=prmMdl.maxNumBits; % 初始化模拟循环参数 tic; nS = 0; % 子帧编号，取值为[0:2:18] Measures = ...

%% AWGN信道 Eb = Energy_txsig/(Nusedlog2(M)Nofdm); SNR = 10.^(SNRdB(ii)/10); %%信噪比换算 sigma = sqrt(Eb/2/SNR); noise_var = Eb/SNR; %噪声方差(功率) noise = randn(NsNofdm,1)+1irandn(NsNofdm,1); rsig_cp = Y_mul + 1sigma*noise; 是什么意思

这段代码实现了一个加性高斯白噪声（AWGN）信道，其中Eb表示每个比特的能量，SNRdB表示信噪比（以分贝为单位）。程序中将SNRdB转化为线性域的信噪比SNR，然后根据式子sigma = sqrt(Eb/2/SNR)计算出噪声的标准差sigma...

%% Set simulation parametrs & initialize parameter structures commlteMIMO_params; [prmLTEPDSCH, prmLTEDLSCH, prmMdl] = commlteMIMO_initialize(txMode, ... chanBW, contReg, modType, Eqmode,numTx, numRx,cRate,maxIter, fullDecode, chanMdl, corrLvl, ... chEstOn, snrdB, maxNumErrs, maxNumBits); clear txMode chanBW contReg modType Eqmode numTx numRx cRate maxIter fullDecode chanMdl corrLvl chEstOn snrdB maxNumErrs maxNumBits %% disp('Simulating the LTE Mode 2: Multiple Tx & Rx antrennas with transmit diversity'); zReport_data_rate(prmLTEPDSCH, prmLTEDLSCH); hPBer = comm.ErrorRate; snrdB=prmMdl.snrdB; maxNumErrs=prmMdl.maxNumErrs; maxNumBits=prmMdl.maxNumBits; %% Simulation loop nS = 0; % Slot number, one of [0:2:18] Measures = zeros(3,1); %initialize BER output while (( Measures(2)< maxNumErrs) && (Measures(3) < maxNumBits)) [dataIn, dataOut, txSig, rxSig, dataRx, yRec, csr] = ... commlteMIMO_TD_step(nS, snrdB, prmLTEDLSCH, prmLTEPDSCH, prmMdl); % Calculate bit errors Measures = step(hPBer, dataIn, dataOut); % Visualize constellations and spectrum if visualsOn, zVisualize( prmLTEPDSCH, txSig, rxSig, yRec, dataRx, csr, nS);end; % Update subframe number nS = nS + 2; if nS > 19, nS = mod(nS, 20); end; end disp(Measures);

首先通过调用函数commlteMIMO_params和commlteMIMO_initialize来设置仿真参数和初始化参数结构。然后通过调用函数zReport_data_rate来输出PDSCH和DLSCH的数据速率。接着定义了一个comm.ErrorRate对象hPBer用于计算...

1．试编写程序，仿真4PAM调制信号在高斯信道下的性能，并与理论分析结果相比。(1）画出两条性能曲线，一条是根据理论平均错误概率画出，另一条是仿真曲线；(2）程序的基本流程：信源产生信息比特、调制、将调制信号送入信道（产生高斯白噪声的程序）、接收端检测、将检测结果与信源原始信息比较计算误符号率和误比特率；(3）在给定信噪比下，第二步需多次重复，以得到一个平均错误概率；(4）信噪比范围：4PAM(0dB-14dB),4QAM(0dB-14dB)，间隔是1dB;也可在 BER =106左右终止。(5)信噪比计算 SNR =10log( Es /N0)=10log( REb /N0)。注意调制不能运用MATLAB内置函数pammod。注意标注中文注释。注意检测方法使用多进制调制信号软输出检测。注意一定用MATLAB编写。编写程序时注意矩阵维度要一致不要出错。注意索引值不能超出数组边界，不要出错。注意仿真曲线不能是直线。

SNRdB = 0:1:14; % 信噪比范围 numBits = 1e6; % 仿真比特数 numSymbols = numBits/2; % 仿真符号数 PAMorder = 4; % PAM调制阶数 QAMorder = 4; % QAM调制阶数 % 生成随机比特序列 bits = randi([0 1],1,numBits);...

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%% AWGN信道 Eb = Energy_txsig/(Nusedlog2(M)Nofdm); SNR = 10.^(SNRdB(ii)/10); %%信噪比换算 sigma = sqrt(Eb/2/SNR); noise_var = Eb/SNR; %噪声方差(功率) noise = randn(NsNofdm,1)+1irandn(NsNofdm,1); rsig_cp = Y_mul + 1sigma*noise; 是什么意思