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A Comparative Study of Biology-inspired and Game Theoretical Optimization Algorithms on Power Utilization Efficiency in Cognitive Radio Environment

by Jide Julius Popoola, Olaoluwa Temitope Ojo
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 12 - Number 13
Year of Publication: 2018
Authors: Jide Julius Popoola, Olaoluwa Temitope Ojo
10.5120/ijais2018451756

Jide Julius Popoola, Olaoluwa Temitope Ojo . A Comparative Study of Biology-inspired and Game Theoretical Optimization Algorithms on Power Utilization Efficiency in Cognitive Radio Environment. International Journal of Applied Information Systems. 12, 13 ( May 2018), 29-36. DOI=10.5120/ijais2018451756

@article{ 10.5120/ijais2018451756,
author = { Jide Julius Popoola, Olaoluwa Temitope Ojo },
title = { A Comparative Study of Biology-inspired and Game Theoretical Optimization Algorithms on Power Utilization Efficiency in Cognitive Radio Environment },
journal = { International Journal of Applied Information Systems },
issue_date = { May 2018 },
volume = { 12 },
number = { 13 },
month = { May },
year = { 2018 },
issn = { 2249-0868 },
pages = { 29-36 },
numpages = {9},
url = { https://www.ijais.org/archives/volume12/number13/1032-2018451756/ },
doi = { 10.5120/ijais2018451756 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T19:09:12.803539+05:30
%A Jide Julius Popoola
%A Olaoluwa Temitope Ojo
%T A Comparative Study of Biology-inspired and Game Theoretical Optimization Algorithms on Power Utilization Efficiency in Cognitive Radio Environment
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 12
%N 13
%P 29-36
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper develops two different optimization algorithms for solving problem of power utilization efficiency in cognitive radio environment (CRE). While genetic algorithm was developed as biology-inspired optimization algorithm, load balancing algorithm was developed as game-theoretical optimization algorithm. The two algorithms were developed in MATLAB environment. The developed algorithms were later evaluated to determine their respective power efficiency utilization in CRE. Numerical results obtained reveal that genetic algorithm is about 15% better than load balancing algorithm in term of power utilization efficiency. In addition, the obtained results show that biology-inspired optimization algorithm such as genetic algorithm in which all the parties act together to optimal system is better candidate for spectral resource allocation in CRE than game-theoretical optimization algorithm such as load balancing algorithm where individual acts separately to optimal the system.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Radio spectrum management dynamic spectrum access optimization evolutionary algorithms game theory

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