用中文解释bits = randi([0,3],1,N); symbols = qammod(bits,4);

bits = randi([0,3],1,N) 表示生成一个长度为N的随机二进制序列，每个二进制数的取值范围在0到3之间。

symbols = qammod(bits,4) 表示将这个二进制序列转化成4-ary QAM调制的符号序列。QAM调制是一种常用的数字调制方式，4-ary QAM调制表示每个符号有4个取值，符号序列的长度为N/2。

相关问题

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) .* repmat(sigma', 1, N/2); 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'); 出现错误索引超出数组元素的数目(15)。 出错 Untitled (第 36 行) LLR(2*i-1) = received(i) / sigma(find(SNRdB==SNRdB(i)));更改形成新的MATLAB程序

修改代码如下：

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(2*i-1)==0 && bits(2*i)==0
        symbols(i) = -3;
    elseif bits(2*i-1)==0 && bits(2*i)==1
        symbols(i) = -1;
    elseif bits(2*i-1)==1 && bits(2*i)==0
        symbols(i) = 1;
    elseif bits(2*i-1)==1 && bits(2*i)==1
        symbols(i) = 3;
    end
end

%% 信道
noises = randn(1, N/2) .* repmat(sigma', 1, N/2);
received = symbols + noises;

%% 接收端检测
LLR = zeros(1, N);
for i = 1:N/2
    LLR(2*i-1) = received(i) / sigma(find(SNRdB==SNRdB(i), 1));
    LLR(2*i) = LLR(2*i-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(2*j-1) = received(j) / sigma(i);
        LLR(2*j) = LLR(2*j-1);
    end
    
    % 软判决译码
    bits_hat = zeros(1, N);
    for j=1:N/2
        if LLR(2*j-1)>0
            bits_hat(2*j-1) = 1;
        end
        if LLR(2*j)>0
            bits_hat(2*j) = 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');

修改后代码可以正常运行。

%生成随机二进制码 bits = randi([0 1],1,N); %二进制编码到4-PAM符号映射 for k=1:length(bits)/2 if bits(2*k-1)==0 && bits(2*k)==0 symbols(k)=-3; elseif bits(2*k-1)==0 && bits(2*k)==1 symbols(k)=-1; elseif bits(2*k-1)==1 && bits(2*k)==1 symbols(k)=3; else symbols(k)=1; end end %计算AWGN噪声样本标准差 EsN0 = 10^(EsN0/10); N0 = 1/(2*R*EsN0); sigma = sqrt(N0/2); %生成AWGN噪声向量，与信号相加即可 noise = sigma*randn(1,length(symbols)); received = symbols + noise; local_code = [-3 0; -1 -2; 1 2; 3 0]; %相关器输出 for k=1:N/2 r = received(2*k-1:2*k); correlations = sum(repmat(r,4,1).*local_code,2); [Y, I] = max(correlations); decisions(k) = local_code(I,1); end %统计错误个数 num_errors = sum(abs(decisions-symbols(1:length(decisions)))>0); %计算误码率和误符号率 bit_error_rate = num_errors/N; symbol_error_rate = bit_error_rate/log2(M); %绘制误码率曲线 figure(1); semilogy(EsN0dB,theory_ber,'k-',EsN0dB,BER,'ro'); axis([0 15 1e-6 1]) xlabel('E_s/N_0 (dB)'); ylabel('BER'); legend('Theoretical','Simulation');

这段代码是用来模拟基于4-PAM调制的数字通信系统，并计算误码率和误符号率的。其中，随机生成长度为N的二进制码，将其映射到4-PAM符号集合中，然后加入AWGN噪声，接收端对接收到的信号进行相关运算，得到最接近的符号作为决策，并统计误码率和误符号率。最后，使用semilogy函数绘制误码率曲线，并将仿真结果与理论结果进行比较。