matlab实现水声通信中的psk方法

clear all; close all Bit_num=2000; Fc=1800; Fs=18000; snr=5; Ts=0.001; t=0:1/Fs:Ts-1/Fs; LenSymbol=length(t); BW=2/Ts; [b,a]=butter(5,2*BW/Fs); Singal_emit=[]; Source=randi(1,Bit_num);%%信源 TEMP=1-2*Source;%%%%%%%%%%%%%%调制 for i_num=1:Bit_num Singal_emit=[Singal_emit TEMP(i_num)*cos(2*pi*Fc*t)]; end % plot(Singal_emit(1:length(t))); % m=0; % for snr=-10:0.5:15 % m=m+1; amp=sqrt(0.5/(10^(snr/10))); %%%%%%%%%加噪声 Signal_rec1=Singal_emit+amp*randn(size(Singal_emit)); % plot(Signal_rec); % vn=randn(1,T)+sqrt(-1)*randn(1,T); % AWGN noise % vn=vn/norm(vn)*10^(-dB/20)*norm(x) % plot(sigaddn); Signal_rec=multipath(Signal_rec1);%%%加多径 % Signal_rec=Singal_emit; Base_wave_real=[]; Base_wave_imag=[]; for i_num=1:Bit_num TEMP1=Signal_rec((i_num-1)*LenSymbol+1:i_num*LenSymbol); % Xk=abs(fft(TEMP,4096)); % index=(0:round(2048-1)); % Xkf=Xk(index+1); % indexf=find(Xkf==max(Xkf)); % Fc=indexf*Fs/4096; % plot(index*Fs/4096,Xkf) % pause % periodogram(TEMP,[],4096,Fs); % pause; TEMP_real=filter(b,a,TEMP1.*cos(2*pi*Fc*t)); % TEMP_real=TEMP1.*cos(2*pi*Fc*t); TEMP_imag=filter(b,a,-1*TEMP1.*sin(2*pi*Fc*t)); % TEMP_real=filter(b,a,TEMP.*cn); % TEMP_imag=filter(b,a,-1*TEMP.*sn); Base_wave_real=[Base_wave_real TEMP_real]; Base_wave_imag=[Base_wave_imag TEMP_imag]; end sample_real=[]; sample_imag=[]; indexn=round(LenSymbol/2); for i_num=1:Bit_num TEMP_base_real=Base_wave_real((i_num-1)*LenSymbol+1:i_num*LenSymbol); TEMP_base_imag=Base_wave_imag((i_num-1)*LenSymbol+1:i_num*LenSymbol); sample_real_temp=TEMP_base_real(indexn); sample_imag_temp=TEMP_base_imag(indexn); % sample_real_temp=sum(TEMP_base_real); % sample_imag_temp=sum(TEMP_base_imag); sample_real=[sample_real sample_real_temp]; sample_imag=[sample_imag sample_imag_temp]; end Sample=sample_real+j*sample_imag; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%求未均衡误码率 g=0; for k=1:Bit_num if sample_real(k)<0 newdata1(k)=1; else newdata1(k)=0; end if newdata1(k)==Source(k) g=g+1; end end Pe1=(Bit_num-g)/Bit_num; %%%%%%%%%%均衡算法（LMS） % TEMP=TEMP+sqrt(-1)*TEMP; trseq=TEMP(1:800); trainlen=length(trseq); inseq=sample_real; % inseq=Sample; lev=40; wei=zeros(lev,1); miu=0.005; index=lev:-1:1; newinseq=[inseq,zeros(1,lev-1)]; scatequ=[]; for n=1:trainlen u=newinseq(index); d(n)=trseq(n); e(n)=d(n)-wei'*u.'; mse(n)=abs(e(n))^2; wei=wei+miu*u.'*e(n)'; index=index+1; end snrout=[]; for n=trainlen+1:length(inseq) u=newinseq(index); y=wei'*u.'; scatequ=[scatequ,y]; snrout=[snrout (abs(TEMP(n)-y))^2]; [pan,pan_equ]=pan_2psk(y); d(n)=pan_equ; e(n)=d(n)-y; mse(n)=abs(e(n))^2; wei=wei+miu*u.'*e(n)'; index=index+1; end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%均衡后判决 g=0; for k=1:Bit_num-trainlen if scatequ(k)<0 newdata(k+trainlen)=1; else newdata(k+trainlen)=0; end if newdata(k+trainlen)==Source(k+trainlen) g=g+1; end end Pe2=(Bit_num-g-trainlen)/(Bit_num-trainlen) % end c=trainlen+1:length(inseq); d=trainlen+1:length(inseq); plot(c,scatequ,'.'); % plot(c,sample_real(d)); xlabel('码元个数'); ylabel('幅度'); % x=-10:0.5:15; % plot(x,Pe1); % hold on % Pe3=Pe2-0.2; % for j=1:length(x) % if Pe3(j)<0 % Pe3(j)=0 % end % end % plot(x,Pe3,'--'); % xlabel('信噪比/dB'); % ylabel('误码率Pe'); % end % x=-10:0.5:15; % % plot(x,Pe1); % % hold on % plot (x,Pe2); % xlabel('SNR/dB'); % ylabel('误码率Pe'); % title('psk在高斯白噪声与多径情况下的误码率性能'); % scatterplot(sample);