I am working on Spectrum Sensing in Cognitive Radio. I want to implement Cyclostationary Feature Detection in Matlab. I had gone through many papers regarding this concept but unfortunately I didn't find any useful paper regarding full formula for theoretical and parameters for simulation. Please suggest some easy papers which is easy to understand and implement for beginners.
Dear sir
Please read this paper
http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1022&context=elecengtheses
and the end you will find matlab code, it could be useful for you
BR
Dear sir
Please read this paper
http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1022&context=elecengtheses
and the end you will find matlab code, it could be useful for you
BR
All you have to do is to compute the autocorrelation of the received signal and set a threshold to check for peaks. See http://arxiv.org/ftp/arxiv/papers/1312/1312.5257.pdf as an example.
Taking the autocorrelation of the received signal and using a threshold will only result in spectrum detection alone and not achieve signal localization. For purpose of cognitive radio, it might be essential to also localize the frequency position of the PU apart from detecting it. Therefore, complete cyclostationarity theory might be required. Consequently, i suggest that you read Gardeners Introduction to Cyclostationary signals....or i could post my codes which i pieced together from the disjointed theories on cyclostationarity. With a little patience, i could do that in the next two days.
@ Djmael
Thanks for the reply. I went through the link you provided. I didn't find any analytic expression of PDF for signal nor any expression for threshold or probabilities. So i think it would be much better if you send me something which has all those basic stuff.
@ Ramy
Thanks for the reply. It would be much better if you provide something genralised. Paper you have provided is very specific and not fruitful in my case in which i want to gain some basic stuff for implementation and its derivation.
@Adeiza
Thanks for the reply. Localization is not a issue in my case as it is assumed to be perfectly known. I am trying to implement cyclostationary detection in simulation and compare it thorough its derivation and analytic expressions. I am also trying to create an particular environment of non Gaussian noise for its feasibility. So if you have something for the beginners then you can forward me in this regard.
Dear sir
find some formula of Pd and Pfa for cyclostationary Feature Detection in this Article
Parallelized cyclostationary feature detection on a software defined radio processor
have you implemanted some thing or not yet??
Best regards
I have Implemented this detector in AWGN channel in Matlab but I am getting vague result. As it performance doesn't vary with change in SNR. Its very strange result for me. I don't know what mistake I am doing in it. I will very grateful if somebody can help me in this. I am attaching my codes please have look and comment.
function S=cyclio_stat_TestStatics(x,N)
lx=length(x);
X=zeros(2*N+1);
Y=zeros(2*N+1);
Ts=1/N;
for f=-N:N
d=exp(-j*2*pi*f*(0:lx-1)*Ts);
xf=x.*d;
n_r=lx:-1:1;
X(f+N+1)=sum(xf(n_r));
Y(f+N+1)=conj(sum(xf(n_r)));
end
alpha=10;
f=5;
f1=f+floor(alpha/2)+(floor(-((N-1)/2)):floor((N-1)/2));
f2=f-floor(alpha/2)+(floor(-((N-1)/2)):floor((N-1)/2));
S=sum(X(f1+N+1).*Y(f2+N+1))/N;
S=abs(S)/lx;
I am a user of cyclostationarity for mechanical systems, so I am not sure if my answer is pertinent. We use statistical tests for detecting the presence of 2nd order cyclostationary components in vibration signals. This is done both in the Envelope spectrum and in full two-dimensional cyclic/spectral indicators. If this is somehow similar to what you are looking for, have a look at my work and the work of Jerome Antoni.
Regards
@ Imtiyaz Khan
Hello sir
I have started working on FPGA Implementation of Cyclostationary Feature Detection. Could you please suggest some easily understandable papers.
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