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)
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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 |
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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 |
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