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https://doi.org/10.20532/cit.2018.1004074

Improved Resource Allocation for TV White Space Network Based on Modified Firefly Algorithm

Kennedy K. Ronoh orcid id orcid.org/0000-0002-2203-7344 ; School of Computing and Informatics, University of Nairobi Nairobi, Keny
George Kamucha ; Department of Electrical and Information Engineering, University of Nairobi Nairobi, Kenya
Thomas O. Olwal orcid id orcid.org/0000-0003-3013-474X ; Department of Electrical Engineering, Tshwane University of Technology, Pretoria, South Africa
Tonny K. Omwansa ; School of Computing and Informatics, University of Nairobi Nairobi, Keny


Puni tekst: engleski pdf 737 Kb

str. 167-177

preuzimanja: 413

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Sažetak

There is continued increased demand for dynamic spectrum access of TV White Spaces (TVWS) due to growing need for wireless broadband. Some of the use cases such as cellular (2G/3G/4G/5G) access to TVWS may have a high density of users that want to make use of TVWS. When there is a high density of secondary users (SUs) in a TVWS network, there is possibility of high interference among SUs that exceeds the desired threshold and also harmful interference to primary users (PUs). Optimization of resource allocation (power and spectrum allocation) is therefore necessary so as to protect PUs against harmful interference and to reduce the level of interference among SUs. Existing resource allocation optimization algorithms for a TVWS network ignore adjacent channel interference, interference among SUs or apply greedy algorithms which result in sub-optimal resource allocation. In this paper we propose an improved resource allocation algorithm based on continuous-binary firefly algorithm. Simulation is done using Matlab. Simulation results show that the proposed algorithm improves the SU sum throughput and SU signal to interference noise(SINR) ratio in the secondary network.

Ključne riječi

dynamic spectrum access; cognitive radio; spectrum allocation; power control

Hrčak ID:

213689

URI

https://hrcak.srce.hr/213689

Datum izdavanja:

18.12.2018.

Posjeta: 878 *