Problem with spectrum sensing using cyclostationary features



I’m currently working on a Cyclostationary Feature Detector (CFD), used
spectrum sensing in a cognitive radio system, as a part of my thesis

I’ve implemented a working prototype in MATLAB and I now want to port it
GNU Radio/USRP1, however I ran into problems.

The algorithm I’ve used to calculate the Spectral Correlation Function
looks something like:

  1. Read n samples into vector z
  2. Multiply vector z with exp(-ipialpha*t) store in x (alpha is the
    frequency, which will take a series of values for each vector z, t is
  3. Multiply vector z with exp(ipialpha*t) store in y
  4. Taper x,y with a Hann-window
  5. Take the N-point FFT of x,y (N < n)
  6. Conjugate X (the FFT of x)
  7. Multiply X* and Y
  8. Repeat from 5 until all n samples are processed and sum up the
    from 7
  9. Normalize the result from 8
  10. Repeat from 2 util the entire series of alpha-values are processed

At the end we’ll end up with a vector of normalized FFTs, which are the
correlations of frequency shifted samples.

Now to the problem, how do I handle the streams with the changing value
alpha? My current thought is to use message queues and blocking threads.
there another (better) way to do this?

I’m thankful for all the input I could get on the coding structure since
new to Python and C++.


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