基于蒙特卡罗仿真的2FSK调制误码性能分析matlab代码

好的，以下是一个基于蒙特卡罗仿真的2FSK调制误码性能分析的MATLAB代码，希望对您有所帮助：

clear all; close all; clc;

% Modulation Parameters
f1 = 1000;           % Frequency of the first tone (in Hz)
f2 = 2000;           % Frequency of the second tone (in Hz)
fs = 10000;          % Sampling frequency (in Hz)
T = 1/fs;            % Sampling period
M = 2;               % Number of symbols
N = 100000;          % Number of bits

% Simulation parameters
SNR_dB_min = 0;      % Minimum SNR value for simulation (in dB)
SNR_dB_max = 20;     % Maximum SNR value for simulation (in dB)
SNR_points = 10;     % Number of SNR values to simulate
sim_runs = 100;      % Number of simulation runs for each SNR value

% Initialize error counters
bit_errors = zeros(SNR_points, sim_runs);
sym_errors = zeros(SNR_points, sim_runs);

% Generate random bits
bits = randi([0 1],N,1);

for k = 1:SNR_points
    SNR_dB = SNR_dB_min + (k-1)*(SNR_dB_max-SNR_dB_min)/(SNR_points-1);
    SNR = 10^(SNR_dB/10);
    A = sqrt(2*SNR*T);
    
    for run = 1:sim_runs
        % Generate random symbols
        symbols = randi([0 M-1],N/2,1);
        
        % Convert symbols to tones
        tones = A*cos(2*pi*f1*T*(symbols==0) + 2*pi*f2*T*(symbols==1));
        
        % Modulate tones and add noise
        received_signal = awgn(sum(tones), SNR_dB, 'measured');
        
        % Demodulate received signal
        demod_signal = received_signal*cos(2*pi*f1*T) - received_signal*cos(2*pi*f2*T);
        demod_signal = demod_signal(1:2:end);
        demod_symbols = (demod_signal > 0);
        
        % Count errors
        bit_errors(k,run) = sum(xor(bits,demod_symbols));
        sym_errors(k,run) = sum(xor(symbols,demod_symbols(1:end-1)));
    end
end

% Compute error rates
bit_error_rate = mean(bit_errors/N);
sym_error_rate = mean(sym_errors/(N/2));

% Plot error rates
figure;
semilogy(SNR_dB_min:(SNR_dB_max-SNR_dB_min)/(SNR_points-1):SNR_dB_max, bit_error_rate, 'o-');
hold on;
semilogy(SNR_dB_min:(SNR_dB_max-SNR_dB_min)/(SNR_points-1):SNR_dB_max, sym_error_rate, 'o-');
grid on;
xlabel('SNR (dB)');
ylabel('Error Rate');
legend('Bit Error Rate', 'Symbol Error Rate');

该代码实现了2FSK调制的蒙特卡罗仿真，并计算了误码率。在仿真过程中，生成随机比特，转换为随机符号并调制为两个正交方波，然后加入高斯白噪声，最后进行解调并计算误码率。最后，将计算出的误码率以对数坐标的形式绘制出来，以便更好地观察误码率随信噪比的变化情况。