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An Intelligent Particle Swarm Optimization for Fuzzy Based Heterogeneous Radio Access Technology (RAT) Selection

An Intelligent Particle Swarm Optimization for Fuzzy Based Heterogeneous Radio Access Technology (RAT) Selection

J. Preethi, S. Palaniswami
Copyright: © 2012 |Volume: 8 |Issue: 4 |Pages: 20
ISSN: 1548-3657|EISSN: 1548-3665|EISBN13: 9781466613027|DOI: 10.4018/jiit.2012100103
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MLA

Preethi, J., and S. Palaniswami. "An Intelligent Particle Swarm Optimization for Fuzzy Based Heterogeneous Radio Access Technology (RAT) Selection." IJIIT vol.8, no.4 2012: pp.23-42. http://doi.org/10.4018/jiit.2012100103

APA

Preethi, J. & Palaniswami, S. (2012). An Intelligent Particle Swarm Optimization for Fuzzy Based Heterogeneous Radio Access Technology (RAT) Selection. International Journal of Intelligent Information Technologies (IJIIT), 8(4), 23-42. http://doi.org/10.4018/jiit.2012100103

Chicago

Preethi, J., and S. Palaniswami. "An Intelligent Particle Swarm Optimization for Fuzzy Based Heterogeneous Radio Access Technology (RAT) Selection," International Journal of Intelligent Information Technologies (IJIIT) 8, no.4: 23-42. http://doi.org/10.4018/jiit.2012100103

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Abstract

The future wireless networks are heterogeneous in nature where different Radio Access Technologies (RATs) coexist in the same coverage area. The user terminal has to select the best access technology among Wireless Local Area Network (WLAN), Wireless Wide Area Network (WWAN), and Universal Mobile Telecommunication Systems (UMTS) etc. at its current location. Thus, selecting the appropriate RAT and cell becomes a complex problem in heterogeneous network due to number of variables involved in the selection process. The main objective of this work in the heterogeneous networks is to maximize the percentage of satisfied users who are assigned to the networks. Henceforth, this paper presents an innovative mechanism for the selection of heterogeneous networks such as WWAN and WLAN. The performance of the proposed algorithm is evaluated using 1000 datasets. From the simulation results, it is found that the proposed algorithm gives highest probability for mobile user satisfaction than the existing methods.

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