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

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.