Energy-Based Bayesian Spectrum Sensing Over η-μ Fading Channels

In this paper, we study the performance of energy detection for spectrum sensing over the eta-mu fading channel, following a Bayesian approach. We derive an infinite series expression for the probability of error, which is a convex combination of false-alarm and signal detection with eta-mu fading. Also, we present an analysis on optimal detection threshold that minimizes the probability of error. The analysis is validated through Monte Carlo simulations, and the performance of the detector for various values of the fading parameters are discussed through numerical techniques. It is observed that the performance degradation is monotone in each of the parameters of the fading distribution. The derived results are useful as the eta-mu fading distribution includes several practically relevant models as special cases.