cp0803_rakeselector.m

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%
% FUNCTION 8.11 : "cp0803_rakeselector"
%
% Simulates channel estimation for a discrete time channel impulse response
% 'hf' with time resolution 'ts' in seconds
% In addition,the function evaluates the weighting factors to be used in a
% RAKE receiver implementing  maximal ratio combing 
% 'fc' is the value of the sampling frequency 
% 'L' is the number of coefficients to be used in the PRake
% 'S' is the number of coefficients to be used in the SRake
%
% The function returns:
% 1) a vector 'G' containing all the amplitude coefficients of the channel
%    impulse response in descending order
% 2) a vector 'T' containing all the relative delays for the elements in
%    vector 'G',i.e.,T(j) represents the relative delay of the multi-path
%    component having amplitude G(j)
% 3) the number 'NF' of non-zero contribution of the channel impulse
%    response
% 4) a vector 'Arake' representing the weighting factors to be used in a
%    ideal RAKE,which processes all the multi-path contributions at the
%    receiver input
% 5) a vector 'Srake' representing the weighting factors to be used in a 
%    SRAKE,which processes the best L multi-path contributions at the
%    receiver input
% 6) a vector 'Srake' representing the weighting factors to be used in a 
%    SRAKE,which processes the best S multi-path contributions at the
%    receiver input
% 7) a vector 'Prake' representing the weighting factors to be used in a
%    PRAKE,which processes the first L multi-path contributions that arrive
%    at the receiver input
%
function [G,T,NF,Arake,Srake,Prake]=cp0803_rakeselector(hf,fc,ts,L,S)
%====================================================================
% Step One - Channel estimation
%====================================================================
dt=1/fc;
ahf=abs(hf);
[s_val,s_ind]=sort(ahf);

NF=0;
i=length(s_ind);
j=0;
%evaluation of the reference vectors for the RAKE combiner
while (s_val(i)>0)&(i>0)
    NF=NF+1;
    j=j+1;
    index=s_ind(i);
    I(j)=index;
    T(j)=(index-1)*dt;
    G(j)=hf(index);
    i=i-1;
end
%===================================================================
% Step Two - Evaluation of the weighting terms
%===================================================================
binsamples=floor(ts/dt);
if S>NF
    S=NF;
end
if L>NF
    L=NF;
end

Arake=zeros(1,NF*binsamples);
Srake=zeros(1,NF*binsamples);
Prake=zeros(1,NF*binsamples);

% SRAKE and all RAKE

for nf=1:NF
    x=I(nf);
    y=G(nf);
    Arake(x)=y;
    if nf<=S
        Srake(x)=y;
    end
end  % for nf=1:NF

% PRAKE
[tv,ti]=sort(T);
TV=tv(1:L);
TI=ti(1:L);
tc=0;
for n1=1:length(TV)
    index=TI(n1);
    x=I(index);
    y=G(index);
    Prake(x)=y;
    tc=tc+1;
    L=L-1;
end