COMPARATIVE ANALYSIS OF THE SPECTRUM SENSING TECHNIQUES

    This project is design based on the paper "Hard Combination Data Fusion for Cooperative Spectrum Sensing in Cognitive Radio".The project presents the performance evaluation of spectrum sensing methods by plotting ROC curve and error probability with SNR for different spectrum sensing methods mentioned below.

  • Energy detector
  • Matched filter
  • Co-variance
  • Eigen Value
  1. Plot ROC curve and total error probability (false alarm+missed detection) vs SNR of these techniques at SNR = 10db and SNR = -10db for Rayleigh noise as well as awgn noise. Create a test signal as per your convenience (we prefer unity signal).
  2. Plot the same by applying cooperative fusion rules to these techniques (AND rule, OR rule, majority rule, average rule). Take the number of sensors as per your convenience.
  3. In cooperative fusion, we use many sensors and fuse their individual results. Here we use a single sensor and make decisions based on the above 4 techniques and fuse the results using the above-mentioned techniques. And plot the same curves mentioned above.

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SIMULATION VIDEO DEMO                                                                                                                                     


You can DOWNLOAD AWGN Error Matlab(p-code) and the reference papers.

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