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

Jide Julius Popoola, Olaoluwa Temitope Ojo in Signal Processing

International Journal of Applied Information Systems
Year of Publication: 2018
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Jide Julius Popoola, Olaoluwa Temitope Ojo
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  1. Jide Julius Popoola and 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):29-36, May 2018. URL, DOI BibTeX

    	author = "Jide Julius Popoola and 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",
    	url = "",
    	doi = "10.5120/ijais2018451756",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


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.


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Radio spectrum management, dynamic spectrum access, optimization, evolutionary algorithms, game theory