Context-aware handover skipping for train passengers in next generation wireless networks

Asad, S. M., Klaine, P. V. , Rais, R. N. B., Mollel, M. S. , Hussain, S. , Abbasi, Q. H. and Imran, M. A. (2023) Context-aware handover skipping for train passengers in next generation wireless networks. Journal of Communications and Networks, 25(3), pp. 285-298. (doi: 10.23919/JCN.2023.000016)

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Abstract

5G spectral efficiency requirements foresee network densification as a potential solution to improve capacity and throughput to target next-generation wireless networks (NGWNs). This is achieved by shrinking the footprint of base stations (BSs), effective frequency reuse, and dynamic use of shared resources between users. However, such a deployment results in unnecessary handovers (HOs) due to the cell size decrements, and limited sojourn time on a high train mobility. In particular, when a train speedily passes through the BS radio coverage footprints, frequent HO rate may result in serious communication interruption impacting quality of service (QoS). This paper proposes a novel context-aware HO skipping that relies on passenger mobility, trains trajectory, travelling time and frequency, network load and signal to interference and noise ratio (SINR) data. We have modelled passenger traffic flows in cardinal directions i.e, north, east, west, and south (NEWS), in a novel framework that employs realistic Poisson point process (PPP) for real-time mobility patterns to support mobile networks. Spatio-temporal simulations leveraging NEWS mobility prediction model with machine learning (ML) where support vector machine (SVM) shows an accuracy of 94.51%. ML-driven mobility prediction results integrate into our proposed scheme that shows comparable coverage probability, and average throughput to the no skipping case, while significantly reducing HO costs.

Item Type:Articles
Additional Information:This work was funded by Deanship of Research and Graduate Studies (DRG), Ajman University under the grant number 2020-IRG-ENIT-10.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Imran, Professor Muhammad and Valente Klaine, Mr Paulo and Asad, Syed and Hussain, Dr Sajjad and Mollel, Dr Michael and Abbasi, Professor Qammer
Authors: Asad, S. M., Klaine, P. V., Rais, R. N. B., Mollel, M. S., Hussain, S., Abbasi, Q. H., and Imran, M. A.
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:Journal of Communications and Networks
Publisher:IEEE
ISSN:1229-2370
ISSN (Online):1976-5541
Published Online:25 May 2023
Copyright Holders:Copyright © 2023 The Authors
First Published:First published in Journal of Communications and Networks 25(3):285 - 298
Publisher Policy:Reproduced under a Creative Commons License

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