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%% SMI Algorithm example 8.7%%
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%----- Givens -----%
K=100;    % Block length
sig2=.001;
d = .5;  % element spacing in terms of wavelength d = lambda/2
N = input('   How many element do you want in uniform linear array?   ');   % number of elements in array
thetaS = input('   What is the desired users AOA (in degrees)?   ');
thetaI = input('   What is the interferers AOA(in degrees)?   ');

%----- Desired Signal & Interferer -----%
T=1E-3;
t=(1:K)*T/K;
S=cos(2*pi*t/T);
thetaS = thetaS*pi/180;                  % desired user AOA
randn('state',5)
I = randn(1,K);  
thetaI = thetaI*pi/180;                    % interferer AOA
n=randn(N,K)*sqrt(sig2);            % calculate noise in each array input

%----- Create Array Factors for each user's signal for linear array -----%

vS = []; vI = [];
i=1:N;
vS=exp(1j*(i-1)*2*pi*d*sin(thetaS));
vI=exp(1j*(i-1)*2*pi*d*sin(thetaI));

%----- Solve for Weights using SMI -----%

x=(vS.'*S+vI.'*I+n);
Rxx=x*x'/K;
r=x*S'/K;
w=inv(Rxx)*r;
w = conj(w./w(1));    % normalize results to first weight
w.'
%----- Plot Results -----%

theta = -pi/2:.01:pi/2;
AF = zeros(1,length(theta));

% Determine the array factor for linear array
e=S(K)-w.'*sum(x,2)/K
for i = 1:N
    AF = AF + w(i).*exp(j*(i-1)*2*pi*d*sin(theta));
end

figure;
plot(theta*180/pi,abs(AF)/max(abs(AF)),'k')
xlabel('AOA (deg)')
ylabel('|AF_n|')
axis([-90 90 0 1.1])
set(gca,'xtick',[-90 -60 -30 0 30 60 90])
grid on