CSI Based Multiple Relay Selection and Transmit Power Saving Scheme for Underlay CRNs Using FRBS and Swarm Intelligence

Kiran Sultan, Ijaz Mansoor Qureshi, Muhammad Atta-ur Rahman, Bassam A. Zafar and Muhammad Zaheer
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Kiran Sultan: Department of CIT, JCC, King Abdulaziz University, Jeddah, Saudi Arabia
Ijaz Mansoor Qureshi: Department of Electrical Engineering, Air University, Islamabad, Pakistan
Muhammad Atta-ur Rahman: College of CS and IT, Department of CS, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
Bassam A. Zafar: Information Systems Department, King Abdulaziz University, Jeddah, Saudi Arabia
Muhammad Zaheer: Department of Electrical Engineering, Air University, Islamabad, Pakistan

International Journal of Applied Metaheuristic Computing (IJAMC), 2019, vol. 10, issue 3, 1-18

Abstract: In this article, a multiple relay selection (MRS) scheme for signal-to-noise ratio (SNR) enhancement is proposed for underlay relay-assisted cognitive radio networks (RCRNs). A secondary source-destination pair experiencing deep fading on direct path is assisted by amplify-and-forward (AF) relays in an underlay mode. In this energy-constrained scenario, the aim is to maximize the secondary network's end-to-end SNR through an intelligent power-saving method incorporated with MRS. In contrast to the prior relay selection (RS) schemes, the relay-selection factor is the difference of SNR of the source-relay link and corresponding relay-destination link for each relay along with its corresponding interference channel coefficient. The difference factor aims to achieve the SNR upper bound while performing minimum power amplification, eventually resulting in interference mitigation as well. The proposed algorithm has been implemented using Fuzzy Rule Based System (FRBS), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and their performance has been compared through simulations.

Date: 2019
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