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Axell, E., Geert, L., Erik, G. and Poor, H.V. (2012) State-of-the-Art and Recent Advances Spectrum Sensing for Cognitive Radio. IEEE Signal Processing Magazine, 29, 101-116.
https://doi.org/10.1109/MSP.2012.2183771

has been cited by the following article:

• TITLE: New Performance Optimization Approach for Cognitive Radio Energy Detection

  AUTHORS: Patrick Dany Bavoua Kenfack, Fabrice Kwefeu Mbakop, Thomas d’Aquin Biyindi

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

  JOURNAL NAME: Open Access Library Journal, Vol.7 No.7, July 28, 2020

  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.