Swarm intelligence based optimization of energy consumption in cognitive radio network

Abstract

The cognitive radio network provides a pioneered solution to the spectrum scarcity problem and represents a new paradigm for designing intelligent wireless networks. Energy efficient cognitive radio system maintaining reliability holds great importance in the present scenario of wireless communications. In a cognitive radio network, relays are used to enhance energy efficiency as well as to maintain the sensing reliability. Most of the works in the area of cognitive radio network focused on optimization of energy consumed during data transmission only, while neglecting the energy consumed during spectrum sensing. In this paper, an energy efficient multi-relay cognitive radio network is designed, in which both sensing energy and data transmission energy are jointly optimized. Also, optimal values of system parameters like sensing time and amplifying gain of the relays are determined for the energy efficient system. The minimization of the energy consumed under constraints of target throughput and sensing requirements of cognitive radio network is considered as an optimization problem. Swarm intelligence based optimization techniques like particle swarm optimization (PSO), Particle Swarm Optimization with Aging Leader and Challengers (ALCPSO), Human behavior based Particle Swarm Optimization (HPSO) and Whale Optimization Algorithm (WOA) are used to optimize energy consumption in the network. The analysis reveals that the proposed scheme makes the cognitive radio network more energy efficient than conventional schemes.