Question

我的BSc最终项目遇到了一些问题，我想知道你是否可以帮助我。

我正在尝试实施基于GSLC方案的数字检测器以及LMS和RLS算法（比较每个人的性能，以及其他人之间的性能）。这是我的问题弹出的时候。我已经成功编写了LMS部分的编程，然而，当谈到RLS时，我陷入了困境。

在查阅了一些参考书目或通过互联网后，我仍然迷失了。在这里，我附上了相应的代码：

 clear all
 clf
 N=6; % Number of antennas
 SNR=20; % SIgnal to noise ratio
 mu=.01; % LMS step
 niter=50000; % Number of iterations
 Npro=10; % Number of promedies

 lambda = 0.99; % Forgetting factor RLS
 delta = 0.001; % Initialization of P(0)

 % Scenario
 a=25/180*pi; % Desired signal
 b1=125/180*pi; % Interferring signal 1
 b2=-90/180*pi; % Interferring signal 2
 g=1; % Gain of our desired signal
 s2n=10.^(-SNR/10); 

 % Definition of signals
 sa=1/sqrt(N)*exp(j*pi*(0:N-1)*sin(a))';
 sb1=1/sqrt(N)*exp(j*pi*(0:N-1)*sin(b1))';
 sb2=1/sqrt(N)*exp(j*pi*(0:N-1)*sin(b2))';

 % Correlation matrices
 Rs=sa*sa';
 Rint=sb1*sb1'+sb2*sb2'+s2n*eye(N);
 Rx=Rs+Rint;

 % Projection and blocking matrices
 A=eye(N);
 A(:,1)=sa;

 % Gram-Schmidt algorithm
 Aort=zeros(size(A));
 Aort(:,1)=A(:,1)/sqrt(real((A(:,1)'*A(:,1))));
 for k1=2:N
    for k2=1:(k1-1)
     Aort(:,k1)=Aort(:,k1)+(Aort(:,k2)'*A(:,k1))*Aort(:,k2);
    end
    Aort(:,k1)=A(:,k1)-Aort(:,k1);
    Aort(:,k1)=Aort(:,k1)/sqrt(real((Aort(:,k1)'*Aort(:,k1))));
 end
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

 C=Aort(:,1); % Restrictions subspace
 B=Aort(:,2:end); % Restrictions' orthogonal subspace
 P_C=C*inv(C'*C)*C';
 P_C_ort=eye(N)-P_C;

 % Optimal solution
 wopt=inv(Rx)*C*inv(C'*inv(Rx)*C)*g;
 wq=sa;

 e_gslc_LMS=zeros(Npro,niter); % Error sequence LMS
 e_gslc_RLS=zeros(Npro,niter); % Error sequence RLS

 % GSLC algorithm
 for kk=1:Npro
    Xa = kron(sa,ones(1,niter)).*kron(ones(N,1),(sign(randn(1,niter))+1i*sign((randn(1,niter)))/sqrt(2)));
    Xb1 = kron(sb1,ones(1,niter)).*kron(ones(N,1),(sign(randn(1,niter))+1i*sign((randn(1,niter)))/sqrt(2)));
    Xb2 = kron(sb2,ones(1,niter)).*kron(ones(N,1),(sign(randn(1,niter))+1i*sign((randn(1,niter)))/sqrt(2)));
    X = Xa + Xb1 + Xb2 + (randn(size(Xa)) + 1i*randn(size(Xa)))/sqrt(2)*sqrt(s2n);

    w_gslc_LMS = zeros(N,niter);
    w_gslc_RLS = zeros(N,niter);
    xa = B'*X;

    wa_LMS = ones(N-1,niter);
    wa_RLS = ones(N-1,niter);

    P = inv(delta)*eye(N-1);

    for k = 2:niter
       y_LMS = X(:,k)'*w_gslc_LMS(:,k-1);
       y_RLS = X(:,k)'*w_gslc_RLS(:,k-1);

       % LMS
       wa_LMS(:,k) = wa_LMS(:,k-1) + mu*xa(:,k)*(X(:,k)'*wq - xa(:,k)'*wa_LMS(:,k-1));

       % RLS
       z = P*xa(:,k);
       alfa = X(:,k)'*wq - xa(:,k)'*wa_RLS(:,k-1); 
       ge = z/(lambda + xa(:,k)'*z);
       P = (P - ge*z')/lambda;
       wa_RLS(:,k) = wa_RLS(:,k-1) + alfa*ge; 
       w_gslc_LMS(:,k) = wq - B*wa_LMS(:,k);
       w_gslc_RLS(:,k) = wq - B*wa_RLS(:,k);
    end
    e_gslc_LMS(kk,:) = sum(abs(w_gslc_LMS - kron(wopt,ones(1,niter))).^2,1)/N;
    e_gslc_RLS(kk,:) = sum(abs(w_gslc_RLS - kron(wopt,ones(1,niter))).^2,1)/N;
 end

 figure(1)
 plot(10*log10(mean(e_gslc_LMS)),'b'), hold on
 plot(10*log10(mean(e_gslc_RLS)),'r')
 grid
 xlabel('Iterations')
 ylabel('dB')
 title('GSLC algorithm - Learning curve of LMS/RLS algorithms')

请你能帮助我找出问题所在吗？非常感谢任何帮助！

GSLC采用LMS / RLS自适应算法

0 个答案: