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New Performance Optimization Approach for Cognitive Radio Energy Detection

DOI: 10.4236/oalib.1106316, PP. 1-11

Subject Areas: Applications of Communication Systems

Keywords: Cognitive Radio, Spectrum Sensing, Energy Detection, Probability of Detection (Pd), Probability of False Alarm (Pfa), Receiver Operating Characteristics (ROC), Python Pandas Library

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Abstract

In this paper, we put forward a new method to deal with energy detection low performance in cognitive radio, especially for small values of signal-to-noise ratio. The method is based on a statistical discrimination of received samples in order to improve probability of detection for a given probability of false alarm. We describe how we have determined discrimination criteria with python pandas library, for a signal-to-noise ratio SNR of 0.5 and a number of samples Ns of 128, assuming Gaussian distribution for noise and useful received signals.

Cite this paper

Kenfack, P. D. B. , Mbakop, F. K. and Biyindi, T. D. (2020). New Performance Optimization Approach for Cognitive Radio Energy Detection. Open Access Library Journal, 7, e6316. doi: http://dx.doi.org/10.4236/oalib.1106316.

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