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Energy Efficiency Optimization of Multiuser Cognitive Radio Network

International Journal of Electronics and Communication Engineering
© 2024 by SSRG - IJECE Journal
Volume 11 Issue 8
Year of Publication : 2024
Authors : Arobindra Saikia, Ashim Jyoti Gogoi
10.14445/23488549/IJECE-V11I8P102
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How to Cite?

Arobindra Saikia, Ashim Jyoti Gogoi, "Energy Efficiency Optimization of Multiuser Cognitive Radio Network," SSRG International Journal of Electronics and Communication Engineering, vol. 11,  no. 8, pp. 11-21, 2024. Crossref, https://doi.org/10.14445/23488549/IJECE-V11I8P102

Abstract:

With the increasing demand for wireless devices in present times, the need for cognitive radio networks has risen. This increases the importance of the energy efficiency of the cognitive radio system. This work investigates the energy efficiency optimization of a multi-user single relay cognitive radio system. Collisions between data packets from numerous secondary users happen in a cognitive radio network, significantly reducing the throughput of the network, which causes a reduction in energy efficiency. This research presents a novel analytical energy efficiency model for the multi-user cognitive radio network. The proposed model makes it easy to formulate an optimization problem in such a way that the energy efficiency can be optimized by maintaining the collision probability within the permissible limit. As a result of this, an improvement in energy efficiency as well as the preservance of reliability of the system in the Cognitive Radio Network (CRN) is obtained. The energy efficiency optimization of the multiuser cognitive radio network is performed using optimization techniques like Particle Swarm Optimization (PSO), Human behavior based Particle Swarm Optimization (HPSO), and Aging Leader and Challengers Particle Swarm Optimization (ALCPSO). The simulation results demonstrate that, in comparison to alternative optimization methods, the optimized systems based on ALCPSO deliver higher energy efficiency. Additionally, a comparison is presented between the proposed method and the existing method for the multi-user cognitive radio system's possible energy efficiency. It is proved by the simulation results and analysis that the scheme proposed here improves the cognitive radio network's energy efficiency.

Keywords:

Energy efficiency, Aging leader and challengers particle swarm optimization, Multi user cognitive radio network, Secondary user, Transmission power.

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