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Load Aware Self-Organising User-Centric Dynamic CoMP Clustering for 5G Networks

Bassoy, S, Jaber, Mona, Imran, Muhammad and Xiao, Pei (2016) Load Aware Self-Organising User-Centric Dynamic CoMP Clustering for 5G Networks IEEE Access, 4. pp. 2895-2906.

CoMP_LoadBalancing_IEEE_final.pdf - Accepted version Manuscript
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Coordinated multi-point (CoMP) is a key feature for mitigating inter-cell interference, improve system throughput and cell edge performance. However, CoMP implementation requires complex beamforming/scheduling design, increased backhaul bandwidth, additional pilot overhead and precise synchronisa-tion. Cooperation needs to be limited to a few cells only due to this imposed overhead and complexity. Hence, small CoMP clusters will need to be formed in the network. In this paper, we first present a self organising, user-centric CoMP clustering algorithm in a control/data plane separation architecture (CDSA), proposed for 5G to maximise spectral efficiency (SE) for a given maximum cluster size. We further utilise this clustering algorithm and introduce a novel two-stage re-clustering algorithm to reduce high load on cells in hotspot areas and improve user satisfaction. Stage-1 of the algorithm utilises maximum cluster size metric to introduce additional capacity in the system. A novel re-clustering algorithm is introduced in stage-2 to distribute load from highly loaded cells to neighbouring cells with less load for multi-user (MU) joint transmission (JT) CoMP case. We show that unsatisfied users due to high load can be significantly reduced with minimal impact on SE.

Item Type: Article
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Bassoy, S
Date : 17 May 2016
DOI : 10.1109/ACCESS.2016.2569824
Copyright Disclaimer : (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 24 May 2016 15:26
Last Modified : 14 Nov 2018 11:19

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