Indoor Mobility Prediction for mmWave Communications using Markov Chain

Turkmen, A., Ansari, S. , Valente Klaine, P. , Zhang, L. and Imran, M. A. (2021) Indoor Mobility Prediction for mmWave Communications using Markov Chain. In: IEEE Wireless Communications and Networking Conference (WCNC 2021), Nanjing, China, 29 March-1 April 2021, ISBN 9781728195056 (doi: 10.1109/WCNC49053.2021.9417348)

[img] Text
228720.pdf - Accepted Version

399kB

Abstract

Millimeter-wave (mm-wave) communication, which has already been a part of the fifth generation of mobile communication networks (5G), would result in ultra dense small cell deployments due to its limited coverage characteristics. To enable seamless handovers between indoor and outdoor environments, a mobility prediction of an indoor user is studied by deploying Markov chains. Based on the effect of external factors on the user’s mobility, a simulation scenario is created to model the trajectory of an indoor user w.r.t the most visited areas before leaving the indoor environment. Based on that, a method for initializing the transition matrix of Markov chains is proposed, via Q-learning. The proposed solution is compared to a standard online learning Markov chain model in terms of different mobility models and learning rates. Results show that the proposed solution is always able to outperform the standard method in terms of prediction accuracy.

Item Type:Conference Proceedings
Additional Information:The first author was supported by the Republic of Turkey Ministry of National Education (MoNE-1416/YLSY).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Ansari, Dr Shuja and Imran, Professor Muhammad and Turkmen, Aysenur and Zhang, Professor Lei and Valente Klaine, Mr Paulo
Authors: Turkmen, A., Ansari, S., Valente Klaine, P., Zhang, L., and Imran, M. A.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
ISSN:1558-2612
ISBN:9781728195056
Published Online:05 May 2021
Copyright Holders:Copyright © 2021 IEEE
First Published:First published in IEEE Wireless Communications and Networking Conference (WCNC 2021)
Publisher Policy:Reproduced in accordance with the publisher copyright policy
Related URLs:

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
300725Distributed Autonomous Resilient Emergency Management System (DARE)Muhammad ImranEngineering and Physical Sciences Research Council (EPSRC)Uncle 12187 - EP/P028764/ENG - Systems Power & Energy