Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/116753
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Type: Journal article
Title: Evaluating performance of RAT selection algorithms for 5G Hetnets
Author: Nguyen, D.
Nguyen, H.
White, L.
Citation: IEEE Access, 2018; 6:61212-61222
Publisher: IEEE
Issue Date: 2018
ISSN: 2169-3536
2169-3536
Statement of
Responsibility: 
Duong D. Nguyen, Hung X. Nguyen and Langford B. White
Abstract: Next generation 5G cellular networks will consist of multiple technologies for devices to access the network at the edge. One of the keys to 5G is, therefore, the ability of devices to intelligently select its radio access technology (RAT). There have been several proposals for RAT selection in the last few years. Understanding the performance and limitation of these RAT selection solutions is important for their deployment in the future 5G heterogeneous networks. In this paper, we provide a taxonomy and comparative performance analysis of recent RAT selection algorithms, including the different network models that were used to evaluate these works. We combine these different network models to build a benchmark for evaluating the RAT selection algorithms in a 5G environment. We implement the representative algorithms of different approaches and cross compare them in our benchmark. From the experiments conducted, we illustrate how the different network parameters, such as the number of base stations visible to a user and the available link bandwidths, could impact the performance of these algorithms.
Keywords: 5G heterogeneous networks; RAT selection; network models; performance evaluation
Rights: © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission.
RMID: 0030100171
DOI: 10.1109/ACCESS.2018.2875469
Appears in Collections:Electrical and Electronic Engineering publications

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