QPSK和4QAM代码.doc

% Default parameters %QOSK NN = 256; % number of symbols tb = 0.5; % bit time p0 = 1; % power fs = 16; % samples/symbol ebn0db = [0:1:15]; % Eb/N0 vector [b,a] = butter(5,1/16); % transmitter filter parameters % % Establish QPSK signals % x = random_binary(NN,fs)+1i*random_binary(NN,fs); % QPSK signal y1 = x; % save signal y2a = y1*sqrt(p0); % scale amplitude % % Transmitter filter % y2 = filter(b,a,y2a); % filtered signal % % Matched filter % b = ones(1,fs); b = b/fs; a = 1; % matched filter parameters y = filter(b,a,y2); % matched filter output % % End of simulation % % Use the semianalytic BER estimator. The following sets % up the semi analytic estimator. Find the maximum magnitude % of the cross correlation and the corresponding lag. % [cor, lags] = vxcorr(x,y); cmax = max(abs(cor)); nmax = find(abs(cor)==cmax); timelag = lags(nmax); theta = angle(cor(nmax)); y = y*exp(-1i*theta); % derotate % % Noise BW calibration % hh = impz(b,a); % receiver impulse response nbw = (fs/2)*sum(hh.^2); % noise bandwidth % % Delay the input, and do BER estimation on the last 128 bits. % Use middle sample. Make sure the index does not exceed number % of input points. Eb should be computed at the receiver input. % index = (10*fs+8:fs:(NN-10)*fs+8); xx = x(index); yy = y(index-timelag+1); [n1, n2] = size(y2); ny2=n1*n2; eb = tb*sum(sum(abs(y2).^2))/ny2; eb = eb/2; [peideal,pesystem] = qpsk_berest(xx,yy,ebn0db,eb,tb,nbw); subplot(1,2,1) yscale = 1.5*max(real(yy)); plot(yy,+) xlabel(Direct Sample); ylabel(Quadrature Sample); grid; axis([-yscale yscale -yscale yscale]) subplot(1,2,2) s