1.完整项目描述和程序获取
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2.部分仿真图预览
3.算法概述
随着通信技术的飞速发展，高阶调制格式如64QAM在高速数据传输中得到了广泛应用。然而，由于信道失真、噪声干扰等因素，接收端往往面临相位偏移和信号失真等问题。为了解决这些问题，基于深度学习的相位检测和补偿算法应运而生。
4.部分源码
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for i = 1:length(SNR)
i
for j = 1:10
[i,j]
%产生信号
signal = round(rand(1,LEN));
signal_modulated1 = Modulator(signal,K);
signal_receive1 = awgn(signal_modulated1,SNR(i),'measured');
signal_receive2 = signal_receive1*exp(sqrt(-1)*phase);
offset2 = func_phase_est_dnn(signal_receive2);%基于深度学习的相位估计
RR = signal_receive2*exp(-sqrt(-1)*mean2(offset2));
%加相位补偿
output = DeModulator(RR,K);
msgr = ones(size(output));
idx = find(output<=0);
msgr(idx) = 0;
len = length(find(signal==msgr));
errrate(i,j)= 1-len/length(signal);
%没有相位补偿
output2 = DeModulator(signal_receive2,K);
msgr2 = ones(size(output2));
idx2 = find(output2<=0);
msgr2(idx2) = 0;
len2 = length(find(signal==msgr2));
errrate2(i,j)= 1-len2/length(signal);
end
end
figure;
semilogy(SNR,mean(errrate2,2),'b-o');
hold on
semilogy(SNR,mean(errrate,2),'r-s');
grid on
xlabel('SNR');
ylabel('误码率');
legend('64QAM无相位补偿误码率','64QAM相位补偿误码率');
0X_042m
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