移动通信实验报告.doc

实验1：AWGN信道中BPSK调制系统的BER仿真计算%Simulation of bpskAWGNMax_SNR=10;N_trials=1000;N=200;Eb=1;ber_m=0; for trial=1:1:N_trials trial msg=round(rand(1,N); % 1, 0 sequence s=1-msg.*2; %0-1, 1-1 n=randn(1,N)+j.*randn(1,N);%generate guass white noise ber_v=; for snr_dB=1:2:Max_SNR snr=10.(snr_dB./10);%snr(db)-snr(decimal) N0=Eb./snr; sgma=sqrt(N0./2); y=sqrt(Eb).*s+sgma.*n; y1=sign(real(y); y2=(1-y1)./2; % 1, 0 sequence error=sum(abs( msg- y2);%error bits ber_snr=error./N;%ber ber_v=ber_v,ber_snr; end %for snrber_m=ber_m+ber_v;endber=ber_m./N_trials; ber_theory=;for snr_db=1:2:Max_SNR snr=10.(snr_db./10); snr_1=Qfunct(sqrt(2*snr); ber_theory=ber_theory,snr_1;end i=1:2:Max_SNR;semilogy(i,ber,-r,i,ber_theory,*b);xlabel(E_b/N_0 (dB)ylabel(BER)legend(Monte Carlo, Theoretic)程序分析：做1000次试验，每次试验取200个抽样点，求出每次试验的误比特率，然后对1000次试验的误比特率取平均值，即得仿真误比特率ber，然后将此误比特率与理论值ber_theory进行比较。程序运行结果如图3所示。图3 bpskAWGN误比特率仿真结果与理论值比较结果分析：由图3可知，仿真结果与理论值基本相符，只是在信噪比较大时，仿真误码率与理论值存在误差，这是因为在高信噪比情况下，误比特率会呈下降趋势，若要仿真实际的误比特率，就需要进行更多次试验，而且每次试验取的抽样点数也应该增加。%Simulation of qpskAWGNN_trials=1000;N_number=100;N_snr=10;Es=1;BER_m=0;SER_m=0; for trials=1:N_trials; trials s10=round(rand(1,N_number); S=(s10*2-1)./sqrt(2); S1=S(1:2:N_number); S2=S(2:2:N_number); Sc=S1+j.*S2;%generate qpsk signal niose=randn(1,N_number/2)+j.*randn(1,N_number/2);%generate noise SER_v=;%Symbol error rate BER_v=;%Bit error rate for snr_db=0:1:N_snr; sgma=(1/2)*sqrt(10.(-snr_db./10); Y=Sc+sgma.*niose; Y_r=sign(real(Y)./sqrt(2); Y_i=sign(imag(Y)./sqrt(2); Y_bit=; for k=1:length(Y_r); Y_bit=Y_bit,Y_r(k),Y_i(k); end; Y_symbol=Y_r+j*Y_i; X_b=S-Y_bit; X_s=Sc-Y_symbol; ber_snr=0; for k=1:N_number if X_b(k)=0; ber_snr=ber_snr+1; end; end; ser_snr=0; for k=1:N_number/2; if X_s(k)=0; ser_snr=ser_snr+1; end; end; BER_v=BER_v,ber_snr./N_number; SER_v=SER_v,ser_snr./(N_number./2); end;%for SNRBER_m=BER_m+BER_v;SER_m=SER_m+SER_v; end % for trials BER=BER_m./N_trials;SER=SER_m./N_trials; BER_T=;SER_T=; for snr_db=0:1:N_snr; snr=10.(snr_db./10); BER_THEORY=Qfunct(sqrt(2.*snr); SER_THEORY=1-(1-(1/2).*erfc(sqrt(snr).2; BER_T=BER_T,BER_THEORY; SER_T=SER_T,SER_THEORY;end; figurei=0:1:N_snr;semilogy(i,BER,-r,i,BER_T,*b);legend(BER-simulation,BER-theory);xlabel(Eb/N0(db);ylabel(BER); figurei=0:1:N_snr;semilogy(i,SER,-g,i,SER_T,*y);legend(SER-simulation,SER-theory);xlabel(E_b/N_0(db);ylabel(SER);程序分析：与bpskAWGN类似，做1000次试验，每次试验取100个点，然后每两个点形成一个qpsk符号，首先计算仿真误比特率和误码率，然后与理论值进行比较。程序运行结果如图4和图5所示，其中图4是ber图，图5是ser图。图4 BER仿真结果与理论值结果分析：由图4和图5可知，在低信噪比的情况下，BER和SER的仿真结果与理论值完全相符，在高信噪比情况下，两者存在差异，这是因为随着信噪比的增加，误比特率和误码率也会增加，这就需要更多的试验次数和更多的抽样点数。将BER和SER仿真结果进行比较可知，在相同信噪比的情况下，BER比SER小，这是因为只要一个比特错，相应的qpsk符号就会出错，而一个qpsk要正确接收，就必须保证它的两个比特全部正确接收。图5 SER仿真结果与理论值实验2：移动通信信道建模与仿真% Simulation Of Jakes Modelclear all;f_max = 30;M = 8; % # of low frequency oscillators - 1N = 4*M+2;Ts=1.024e-04;sq = 2/sqrt(N);sigma = 1/sqrt(2);theta = 0; % Fixed Phasecount = 0;t0=0.001; for t = 0:Ts:0.5 % Varying time count = count + 1 g(count) = 0; for n = 1 : M+1, if n = M c_q(count,n) = 2*sigma*sin(pi*n/M); % Gain associated with quadrature component c_i(count,n) = 2*sigma*cos(pi*n/M); % Gain associated with inphase component f_i(count,n) = f_max*cos(2*pi*n/N); % Discrete doppler frequencies of inphase component f_q(count,n) = f_max*cos(2*pi*n/N); % Discrete doppler frequencies of quadrature component else c_i(count,n) = sqrt(2)*cos(pi/4); c_q(count,n) = sqrt(2)*sin(pi/4); f_i(count,n) = f_max; f_q(count,n) = f_max; end; % end if g_i(count,n) = c_i(count,n)*cos(2*pi*f_i(count,n)*(t-t0) + theta); % Inphase component for one oscillator g_q(count,n) = c_q(count,n)*cos(2*pi*f_q(count,n)*(t-t0) + theta); % Quadrature component for one oscillator end; %end n tp(count) = sq*sum(g_i(count,1:M+1);% Total Inphase component tp1(count) = sq*sum(g_q(count,1:M+1);% Total quadrature component end; % end count no n again envelope=sqrt(tp.2+tp1.2);%rayleigh envelope rmsenv=sqrt(sum(envelope.2)/count);%root mean square envelpe auto_i,lag_i = xcorr(tp,coeff) ; % Auto-correlation associated with inphase component auto_q,lag_q = xcorr(tp1,coeff); % Auto-correlation associated with quadrature component len=length(lag_i); corrx2,lag2 = xcorr(tp,tp1,coeff);% Cross Correlation between inphase and quadrature components aa=-(len-1)/2:1:(len-1)/2;%total duration for lag bb=(len-2001)./2;%mid . points for drawing figures cc=bb+1:1:bb+2001;%for getting the mid-values dd=-1000:1:1000; %_ tdd=dd*Ts; z=2.*pi.*f_max*tdd; sigma0=1; T_bessel=sigma0.2.*besselj(0,z); % figure; plot(tdd,auto_i(cc),-,tdd,T_bessel,*);%in-phase xlabel(t(Second); ylabel(Auto-correlation); legend(In-component) figure; plot(tdd,auto_q(cc),-,tdd,T_bessel,*);%quadrature xlabel(t(Second); ylabel(Auto-correlation); legend(Q-component) figureco1=1:1000; semilogy(co1*Ts,envelope(1:1000);xlabel(t(Second);ylabel(Rayleigh Coef.);%_length_r=length(envelope); %_pdf_env=zeros(1,501); count=0;temp=round(100.*envelope);for k=1:length_r if temp(k)-1, 1-1 %pn01=round(rand(1,Q); pn=pn_m(15,1)./sqrt(15); %pn:1 by 15 matrix %pn=(pn01.*2-1)./sqrt(Q); s=kron(ss,pn); %s:1 by 1500 matrix sgma=1; Error_v= ; for snr_db=0:1:N_snr snr=10.(snr_db./10); N0=2*sgma.2; Eb=snr.*N0; yy=sqrt(Eb)*s+noise; Y_M= ; for k=1:N_number ym=yy(1,(k-1)*Q+1:k*Q); %Get yys every 15 points Y_M=Y_M;ym; %Y_M:100 by 15 matrix end ys=Y_M*pn.; %ys:100 by 1 matrix y=ys.; y_real=real(y); s_e=sign(y_real); s_e10=(s_e+1)./2; Error_snr=sum(abs(s10-s_e10); Error_v=Error_v,Error_snr./N_number; end E_M=E_M;Error_v ;end BER=mean(E_M); BER_T= ; for snr_db=0:1:N_snr snr=10.(snr_db./10); BER_THEROY=Qfunct(sqrt(2.*snr); BER_T=BER_T,BER_THEROY; end lpa=1i=0:1:N_snr;semilogy(i,BER,-r,i,BER_T ,*g);xlabel(E_b/N_0(dB)ylabel(BER)legend(Simulated, Theoretic);程序分析：做1000次试验，每次选取100个二进制信号，扩频增益Q为15，调用pn序列形成函数pn_m.m产生15为pn序列，然后调用kron函数求得信号与pn序列的乘积，从而求得发送扩频信号s，然后产生噪声，进而获得接收信号yy，接着将yy的每15个点组成一个向量ym并存入矩阵Y_M中，这样，Y_M中每一行就是接收到的加噪后的扩频信号，然后将每一行乘以pn序列（即扩频码）进行解扩，得到未扩频的信号。最后计算误比特率，并和理论值进行比较。程序运行结果如图10所示。图10 AWGN信道中bpsk扩频系统BER仿真结果与理论图形结果分析：由图10可知，在低信噪比情况下，BER的仿真结果与理论值完全吻合，当信噪比增大到9dB以上时，由于误码率大大减小，而程序中的取样点数和试验次数又没有相应增加，因此BER仿真值不能准确计算，从而未能在图10中显示出来。%main file2：ssbpskflat.mglobal speedMax_SNR=20;ber_m=;N_trial=1000;N=100;Q=8;k_user=2;for trial=1:N_trial trial %_ % the channel fs=20.*1e+6; Ts=1./fs; Fc=2.4*1e+9; c=3*10.8; lambda=c./Fc; speed=10; %km/h fd=(speed./3.6)./lambda; NN=25; rayleigh_parameter=rayleigh_init_med(NN,lambda,Ts); %generate rayleigh_parameter Envelope_M=; for k=1:k_user %fad=flat(N,fd,fs); fad= rayleigh_fading(path,rayleigh_parameter,N); %generate rayleigh envelop %rmsfad=sqrt(mean(abs(fad).2); envelope=kron(abs(fad),ones(1,Q); %convert matrix dimensions Envelope_M=Envelope_M;envelope;end pn=(2.*round(rand(k_user,Q)-1)./sqrt(Q); msg=round(rand(k_user,N); % 1, 0 sequence msg01=msg(1,:); ss=1-msg.*2 ; %0-1, 1- -1 %_ dataspread=; for k=1:k_user dk=ss(k,:); pnk=pn(k,:); dataspread=dataspread;kron(dk,pnk); end noise=randn(1,Q.*N)+j.*randn(1,Q.*N); ber_v=; sgma=1; for snr_db=1:2:Max_SNR snr1=10.(snr_db./10); N0=sgma.2.*2; Eb1=snr1.*N0; snr2_db=15; snr2=10.(snr2_db./10); Eb2=snr2.*N0; if k_user=3 error(only no more than 2 users) end if k_user=1 AM=sqrt(Eb1); else AM=sqrt(Eb1),sqrt(Eb2); end sig_r=AM*(Envelope_M.*dataspread); yspread=sig_r+sgma.*noise; DE_M=; for kk=1:N ykk=yspread(1,(kk-1).*Q+1:kk.*Q); DE_M=DE_M;ykk; end pn0=pn(1,:); de_data=DE_M*pn0.; y=sign(real(de_data.); y01=(1-y)./2; % 1, 0 sequence error=sum(abs( msg01- y01); ber_snr=error./(N); ber_v=ber_v,ber_snr; end %for snr ber_m=ber_m;ber_v;end %for trialber=mean(ber_m); ber_theory=; for snr_dB=1:2:Max_SNR; snr=10.(snr_dB./10);