Fuzzy Q-Learning-Based User-Centric Backhaul-Aware User Cell Association Scheme

Pervez, F., Jaber, M., Qadir, J., Younis, S. and Imran, M. A. (2017) Fuzzy Q-Learning-Based User-Centric Backhaul-Aware User Cell Association Scheme. In: 13th International Wireless Communications and Mobile Computing Conference (IWCMC), Valencia, Spain, 26-30 June 2017, pp. 1840-1845. ISBN 9781509043729 (doi: 10.1109/IWCMC.2017.7986564)

Abstract

Heterogeneous networks are a key solution to serving the exponential surge in data volume and higher quality expectations. Nonetheless, such networks require the ubiquitous presence of fiber-to-the-cell to address the performance demands of 5G and fast-spreading small cells. To this end, innovative ways of optimizing the usage of realistic backhaul links are being investigated. In this work, we propose a fuzzy Q-learning-based user-centric backhaul-aware user cell association scheme. The proposed scheme aims at optimizing the user-cell association process in a context-aware and backhaul-aware manner. Complementing the scheme with fuzzy-logic requires 33.3% additional storage memory. On the other hand, it increases the computational efficiency by 60% and improves the users' performance by 12%.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Imran, Professor Muhammad
• Authors: Pervez, F., Jaber, M., Qadir, J., Younis, S., and Imran, M. A.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• ISSN: 2376-6506
• ISBN: 9781509043729
• Copyright Holders: Copyright © 2017 IEEE
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher