4QAm.rar_4QAM_误差_误差分析

clear N = 10^5; % number of symbols Es_N0_dB = [-3:20]; % multiple Eb/N0 values ipHat = zeros(1,N); for ii = 1:length(Es_N0_dB) ip = (2*(rand(1,N)>0.5)-1) + j*(2*(rand(1,N)>0.5)-1); % s = (1/sqrt(2))*ip; % normalization of energy to 1 n = 1/sqrt(2)*[randn(1,N) + j*randn(1,N)]; % white guassian noise, 0dB variance y = s + 10^(-Es_N0_dB(ii)/20)*n; % additive white gaussian noise % demodulation y_re = real(y); % real y_im = imag(y); % imaginary ipHat(find(y_re < 0 & y_im < 0)) = -1 + -1*j; ipHat(find(y_re >= 0 & y_im > 0)) = 1 + 1*j; ipHat(find(y_re < 0 & y_im >= 0)) = -1 + 1*j; ipHat(find(y_re >= 0 & y_im < 0)) = 1 - 1*j; nErr(ii) = size(find([ip- ipHat]),2); % couting the number of errors end simSer_QPSK = nErr/N; theorySer_QPSK = erfc(sqrt(0.5*(10.^(Es_N0_dB/10)))) - (1/4)*(erfc(sqrt(0.5*(10.^(Es_N0_dB/10))))).^2; close all figure semilogy(Es_N0_dB,theorySer_QPSK,'b.-'); hold on semilogy(Es_N0_dB,simSer_QPSK,'mx-'); axis([-3 15 10^-5 1]) grid on legend('theory-QPSK', 'simulation-QPSK'); xlabel('Es/No, dB') ylabel('Symbol Error Rate') title('Symbol error probability curve for QPSK(4-QAM)')