Performance Enhancement of Underlay Cognitive Radio Networks by Intelligent Multiple Relay Selection

Abstract

In an underlay spectrum sharing environment, relay selection stands as one of the fascinating techniques to address the challenge of performance enhancement of secondary communication via cognitive relays. In this paper, a similar constrained optimization problem is discussed in which a secondary source-destination pair is assisted by a potential Relay assisted Cognitive Radio (RCRN) in the worst-case scenario when line-of-sight (LOS) path is not available to enable the communication. In order to solve this sophisticated problem, we perform multiple relay selection under the assumption of availability of perfect channel state information (CSI) and propose two novel techniques, one based on Artificial Bee Colony (ABC) evolutionary computing and the second based on Fuzzy Rule Based System (FRBS). Both proposed techniques aim to maximize the signal-to-noise ratio (SNR) at the destination keeping in view the transmit power and interference constraints. The effectiveness of the schemes is highlighted through simulation results, along with their comparison.