A Comprehensive Analysis of Spectrum Sensing Methods in Cognitive Radio Networks

Author(s)	Aparna Singh Kushwah, Vineeta Saxena Nigam
Country	India
Abstract	Optimum use of the spectrum is based on the observation of primary signal present in the spectrum. Various methods are defined in the literature for signal detection. The work presented in this paper is about the performance of different spectrum sensing methods. A comparative analysis the performance of energy detection, matched filter detection, co-variance detection and cyclo-stationary feature detection is done using MATLAB simulations. These methods have their own pros and cons. Computer simulations show that matched filter detection gives the maximum value of detection probability, thus proving the best method to sense the channel for the presence of primary signal. It is observed and verified that matched filter detection is the most efficient type of spectrum sensing method in terms of detection probability.
Keywords	Energy Detection, Matched Filter Detection, Co-variance Detection, Cyclo-stationary Feature Detection, Cognitive Radio Network
Field	Computer > Network / Security
Published In	Volume 3, Issue 3, May-June 2021
Published On	2021-05-17
Cite This	A Comprehensive Analysis of Spectrum Sensing Methods in Cognitive Radio Networks - Aparna Singh Kushwah, Vineeta Saxena Nigam - IJFMR Volume 3, Issue 3, May-June 2021.

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International Journal For Multidisciplinary Research