Matlab模拟基于M2M4的频谱感知算法仿真

%---------------------------------M2M4_8PSK------------------------------------- clear all; clc; N=[200 500 2000 5000]; %data length Ns=100; %experiment time snr_theory = -10:25; % Theoretical value of SNR h=waitbar(0,'please wait...'); % Generate data. M = 8; % 8PSK modulation order ini_phase = pi/4; %ini_phase s2_theory=10.^(-snr_theory/10); for m = 1:length(snr_theory) waitbar(m/length(snr_theory)); for j=1:4 for n=1:Ns x = randi([0,M-1],N(j),1); % Random bit stream psksig = pskmod(x,M,ini_phase); % PSK signal rxsig = awgn(psksig,snr_theory(m),'measured'); % Add Gaussion noise M2 = mean(rxsig.*conj(rxsig)); % Two order Moments M4 = mean((rxsig.*conj(rxsig)).^2); % Four order Moments s1_est(n) = sqrt(abs(2*M2.^2-M4)); %S,signal power estimation s2_est(n) = M2-s1_est(n); %N,noise power estimation STD_s2(j,m)=sqrt(var(s2_est)); %standard deviation est_s2(j,m)=mean(s2_est); %estimation value end end end close(h); figure(1) %plot estimation value plot(s2_theory,s2_theory); hold on; plot(s2_theory,est_s2(1,:),'r-o'); hold on; plot(s2_theory,est_s2(2,:),'b-*'); hold on; plot(s2_theory,est_s2(3,:),'r-^'); hold on; plot(s2_theory,est_s2(4,:),'k->'); hold off figure(2) % plot estimation STD plot(snr_theory,STD_s2(1,:),'r-o'); hold on; plot(snr_theory,STD_s2(2,:),'b-*'); hold on; plot(snr_theory,STD_s2(3,:),'r-^'); hold on; plot(snr_theory,STD_s2(4,:),'k->'); grid on;