Entropy detection approach applying random sampling in cognitive radio systems

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Abstract Currently, the spectrum sensing is an active research area in cognitive radio systems that aims to identify the presence or absence of a primary user in a specific frequency band. The challenge of each spectrum sensing technique is to reach a maximum of detection probability for a given false alarm probability and to detect the presence/absence in very low signal to noise ratio regions. In the present work, we endeavor to improve the performance of detection by investigating entropy detection associated with random sampling. The performance of the proposed approach is evaluated in terms of Receiver Operating Characteristic and the reconstruction Signal to Noise Ratio of the detected signal. The obtained results are compared to the uniform sampling case to present the advantages of the random sampling.

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