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.