Unified Analysis of Cooperative Spectrum Sensing over Composite and Generalized Fading Channels

TL;DR

This paper provides a unified analytical framework for evaluating cooperative spectrum sensing performance over various composite and generalized fading channels, accounting for imperfect feedback and optimizing node configurations.

Contribution

It introduces a generalized closed-form expression for energy detection probability over complex fading models and derives optimal node and antenna configurations to minimize total error rate.

Findings

Derived a generalized closed-form for detection probability.

Identified the TER floor with imperfect feedback channels.

Optimized the number of antennas to minimize error rate.

Abstract

In this paper, we investigate the performance of cooperative spectrum sensing (CSS) with multiple antenna nodes over composite and generalized fading channels. We model the probability density function (PDF) of the signal-to-noise ratio (SNR) using the mixture gamma (MG) distribution. We then derive a generalized closed-form expression for the probability of energy detection, which can be used efficiently for generalized multipath as well as composite (multipath and shadowing) fading channels. The composite effect of fading and shadowing scenarios in CSS is mitigated by applying an optimal fusion rule that minimizes the total error rate (TER), where the optimal number of nodes is derived under the Bayesian criterion, assuming erroneous feedback channels. For imperfect feedback channels, we demonstrate the existence of a TER floor as the number of antennas of the CR nodes increases. Accordingly, we derive the optimal rule for the number of antennas that minimizes the TER. Numerical and Monte-Carlo simulations are presented to corroborate the analytical results and to provide illustrative performance comparisons between different composite fading channels.