Paper Info
Title
Energy-based Bayesian spectrum sensing over α-μ / stacy / generalized gamma fading channels.
Abstract
In this paper, we study the performance of energy detection for spectrum sensing over α-μ (a rewritten form of the Stacy or the generalized gamma) fading channels, following a Bayesian approach. We derive an infinite series expression for the probability of error, which is a convex combination of probabilities of false-alarm and signal detection. Also, we present an analysis on the optimal detection threshold that minimizes the probability of error. The analysis is validated through Monte Carlo simulations, and the performance of the detector for different values of the parameters α and μ are discussed. The derived results are useful as the α-μ fading distribution includes several practical fading models such as Rayleigh, Nakagami-m, and Weibull distributions, as special cases.
Year
Venue
Field
2016
COMSNETS
Statistical physics,Monte Carlo method,Rayleigh fading,Convex combination,Computer science,Fading,Weibull fading,Real-time computing,Fading distribution,Statistics,Rician fading,Channel state information
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
1
Name
Order
Citations
PageRank
Sanjeev Gurugopinath143.79