Memory-based user-centric backhaul-aware user cell association scheme

Pervez, F., Jaber, M., Qadir, J., Younis, S. and Imran, M. A. (2018) Memory-based user-centric backhaul-aware user cell association scheme. IEEE Access, 6, pp. 39595-39605. (doi: 10.1109/ACCESS.2018.2850752)

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Ultra dense small cell networks represent a key future network solution that can help meet the exponentially rising traffic requirements of modern wireless networks. Backhauling these small cells is an emerging challenge to the extent that various cells are likely to have different backhaul constraints. The user-centric backhaul scheme has been proposed in the literature to jointly exploit the diversity in users’ requirement and backhaul constraints. In this work, we propose a novel scheme, termed the Memory-based Hybrid Scheme, that additionally also exploits the predictability in a users mobility. We compare the novel scheme to two variants of memory-less user-centric backhaul implementations and show significant gains in convergence time (15%), user-centric KPIs (51% and 82%) at the negligible cost 2% loss in cumulative throughput. The novel scheme requires additional memory in user-devices to store learned values, which is nonetheless well justified in view of the considerable gains achieved.

Item Type:Articles
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
Journal Name:IEEE Access
ISSN (Online):2169-3536
Published Online:19 July 2018
Copyright Holders:Copyright © 2018 IEEE
First Published:First published in IEEE Access 6: 39595-39605
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
3007250Distributed Autonomous Resilient Emergency Management System (DARE)Muhammad ImranEngineering and Physical Sciences Research Council (EPSRC)EP/P028764/1ENG - Systems Power & Energy