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sa_fig4_13.m

%Smart Antennas figure 4.13 Blackman weights on a linear array d=.5; N=input('what is the number of elements?'); theta=-pi/2:.01:pi/2; ang=theta*180/pi; test=blackman(N); check=mod(N,2) if chec

sa_ex8_2.m

%Maximum SIR beamforming % example 8.2 d=.5; N=3; sig2=.001; % noise variance theta=-pi/2:.01:pi/2; ang=theta*180/pi; th0=pi/6; % receive angle th1=-pi/6; % first interfer

sa_ex8_13.m

%%%%%%%%%%%%%%%%%%% %% Conjugate Gradient %% %%%%%%%%%%%%%%%%%%% %----- Givens -----% K=20; % total number of data samples sig2=.001; d = .5; % element spacing in terms of wavelength d = l

sa_fig3_16.m

% Smart Antennas figure 3.16 calculate the polar patterns for the finite length dipole and the 3-D patterns % Lolam= L/lambda; th=-pi:.01:pi; lolam=.5:.5:1.5; u1=((cos(pi*lolam(1)*cos(th))-cos(pi*

sa_fig3_17.m

% Smart Antennas Figure 3.17 plotting the directivity vs. finite dipole length in wavelengths F=inline('((cos(pi*ll*cos(x))-cos(pi*ll))./sin(x)).^2.*sin(x)') delta=.01; x=delta:delta:pi; for i

sa_fig3_7.m

% Smart antennas figure 3.7. 3-D pattern for cos(theta)^4 pattern % use 100 data points in theta and 100 data points in phi tend=pi/2; set(0,'defaultfigurecolor','w') fx=inline('abs(sin(3*pi*sin

sa_ex8_1.m

%Godara Method % Example 8.1 d=.5; N=5; sig2=.001 theta=-pi/2:.01:pi/2; ang=theta*180/pi; th0=0; % receive angle th1=-15*pi/180; % first interferer angle th2=25*pi/180;

sa_fig6_25.m

% Angular distribution for a circle of scatterers thmax=pi/4; th=-pi/4:pi/400:pi/4; f=2*sqrt(thmax^2-th.^2)/thmax^2; figure; plot(th*180/pi,f,'k') xlabel('Arrival Angle') Ylabel('PAP') axis(

sa_fig4_24.m

% Smart Antennas figure4.24 plotting elevation plane pattern a=1; N=10; pinc=2*pi/N; th=-pi/2:.01:pi/2; th0=pi/6; ph0=0; AF=zeros(1,length(th)); for n=1:N AF=AF+exp(-1j*2*pi*a*(sin(th

sa_fig6_22.m

% Angular distribution for a circle of scatterers thmax=pi/4; th=-pi/4+.01:.001:pi/4-.01; f=1./sqrt(thmax^2-th.^2); figure; plot(th*180/pi,f,'k') xlabel('Arrival Angle') Ylabel('PAP') axis([