Performance Analysis and Optimization of Bidirectional Overlay Cognitive Radio Networks with Hybrid-SWIPT

TL;DR

This paper analyzes and optimizes a bidirectional cognitive radio network with hybrid SWIPT, focusing on energy harvesting, relay cooperation, and spectrum sharing to improve throughput and energy efficiency.

Contribution

It introduces a comprehensive performance analysis of a bidirectional overlay cognitive radio network with hybrid SWIPT and proposes an optimization approach using particle swarm optimization.

Findings

Derived outage probability expressions under Nakagami-m fading.

Optimized system parameters for maximum throughput and energy efficiency.

Simulation results validate the analytical models and optimization effectiveness.

Abstract

This paper considers a cooperative cognitive radio network with two primary users (PUs) and two secondary users (SUs) that enables two-way communications of primary and secondary systems in conjunction with non-linear energy harvesting based simultaneous wireless information and power transfer (SWIPT). With the considered network, SUs are able to realize their communications over the licensed spectrum while extending relay assistance to the PUs. The overall bidirectional end-to-end transmission takes place in four phases, which include both energy harvesting (EH) and information transfer. A non-linear energy harvester with a hybrid SWIPT scheme is adopted in which both power-splitting and time-switching EH techniques are used. The SUs aid in relay cooperation by performing an amplify-and-forward operation, whereas selection combining technique is adopted at the PUs to extract the intended signal from multiple received signals broadcasted by the SUs. Accurate outage probability expressions for the primary and secondary links are derived under the Nakagami-$m$ fading environment. Further, the system behavior is analyzed with respect to achievable system throughput and energy efficiency. Since the performance of the considered system is strongly affected by the spectrum sharing factor and hybrid SWIPT parameters, particle swarm optimization is implemented to optimize the system parameters so as to maximize the system throughput and energy efficiency. Simulation results are provided to corroborate the performance analysis and give useful insights into the system behavior concerning various system/channel parameters.