3D Transition Matrix Solution for a Path Dependency Problem of Markov Chains-Based Prediction in Cellular Networks

Ozturk, M., Valente Klaine, P. and Imran, M. A. (2018) 3D Transition Matrix Solution for a Path Dependency Problem of Markov Chains-Based Prediction in Cellular Networks. In: IEEE VTC 2017 BackNets Workshop, Toronto, Canada, 24-27 Sept 2017, ISBN 9781509059355 (doi: 10.1109/VTCFall.2017.8288350)

Abstract

Handover (HO) management is one of the critical challenges in current and future mobile communication systems due to new technologies being deployed at a network level, such as small and femtocells. Because of the smaller sizes of cells, users are expected to perform more frequent HOs, which can increase signaling costs and also decrease user's performance, if a HO is performed poorly. In order to address this issue, predictive HO techniques, such as Markov chains (MC), have been introduced in the literature due to their simplicity and generality. This technique, however, experiences a path dependency problem, specially when a user performs a HO to the same cell, also known as a re-visit. In this paper, the path dependency problem of this kind of predictors is tackled by introducing a new 3D transition matrix, which has an additional dimension representing the orders of HOs, instead of a conventional 2D one. Results show that the proposed algorithm outperforms the classical MC based predictors both in terms of accuracy and HO cost when re-visits are considered.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Imran, Professor Muhammad and Öztürk, Metin and Valente Klaine, Mr Paulo
• Authors: Ozturk, M., Valente Klaine, P., and Imran, M. A.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• ISBN: 9781509059355
• Copyright Holders: Copyright © 2017 IEEE
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher

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