kalman_d.m

比较LMS

%Kalman_S.m
%Kalman algorithm
%static status
%synchronous CDMA
%channel: White Gaussis Noise

function [P1,P_i_n,y,correct,E_ex,KK,w] = Kalman_D(b,N,K,step,yN_step,S,SS,C_null,SNR,KK,w)

% %initial
% C(1,:)=SS(1,:);
% C(2:N,:)=rand(N-1,N)*2-1;
% for i=2:N
%     rou=C(i,:)*C(1:i-1,:).'./dot(C(1:i-1,:),C(1:i-1,:),2).';
%     C(i,:)=C(i,:)-rou*C(1:i-1,:);
% end
% for i=1:N
%     C(i,:)=C(i,:)/sqrt(dot(C(i,:),C(i,:)));
% end
% C_null=C(2:N,:);

%KK=eye(N-1);
%w=zeros(N-1,1);
%c=S(1,:).';%N×1
c=zeros(N,1);
%multiuser detection
for i=1:step
    d=C_null*yN_step(:,i);%(N-1)×1
    %E_min=(c.'*yN_step(:,i))^2;
    g=KK*d*(d.'*KK*d+1)^(-1);
    KK=KK-g*d.'*KK;
    yy=S(1,:)*yN_step(:,i);
    w=w+g*(yy-d.'*w);
    c=S(1,:).'-C_null.'*w;
    
    P1(i)=(c.'*S(1,:).')^2;
    P_i_n(i)=( c.'*(yN_step(:,i)-b(1,i)*S(1,:).') )^2;
    %SINR(i)=P1/P_i_n;
    
    y(i)=sign(c.'*yN_step(:,i)); 
    
    E=(c.'*yN_step(:,i)/N)^2;
    E_min=1;
    E_ex(i)=E-E_min;
end
correct=(y==b(1,:));

%plot(SINR);