Bassoy, S., Jaber, M., Imran, M. A. and Xiao, P. (2016) Load aware self-organising user-centric dynamic CoMP clustering for 5G networks. IEEE Access, 4, pp. 2895-2906. (doi: 10.1109/ACCESS.2016.2569824)
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Abstract
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 synchronization. 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-organizing, user-centric CoMP clustering algorithm in a control/data plane separation architecture, proposed for 5G to maximize spectral efficiency (SE) for a given maximum cluster size. We further utilize 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 utilizes 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 neighboring cells with less load for multi-user joint transmission CoMP case. We show that unsatisfied users due to high load can be significantly reduced with minimal impact on SE.
Item Type: | Articles |
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Additional Information: | This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) within the iCASE Award through the British Telecom under Grant 1511412 and in part by U.K. EPSRC under Grant EP/N020391/1. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Imran, Professor Muhammad |
Authors: | Bassoy, S., Jaber, M., Imran, M. A., and Xiao, P. |
College/School: | College of Science and Engineering > School of Engineering |
Journal Name: | IEEE Access |
Publisher: | IEEE |
ISSN: | 2169-3536 |
ISSN (Online): | 2169-3536 |
Copyright Holders: | Copyright © 2016 IEEE |
First Published: | First published in IEEE Access 4: 2895-2906 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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