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Joint processing coordinated multipoint transmission (JP-CoMP) has gained high attention as part of the effort to cope with the increasing levels of demand in the next-generation wireless communications systems. By clustering neighboring cells and with cooperative transmission within each cluster, JP-CoMP efficiently mitigates inter-cell interference and improves the overall system throughput. However, choosing the optimal clustering is formulated as a nonlinear mathematical problem, making it very challenging to find a practical solution. In this paper, we propose a distributed cell clustering algorithm that maximizes the overall throughput of the JP-CoMP scheme. The proposed algorithm renders the nonlinear mathematical problem of JP-CoMP clustering into an approximated linear formulation and introduces a multi-layer message-passing framework in order to find an efficient solution with a very low computational load. The main advantages of the proposed algorithm are that i) it enables distributed control among neighboring cells without the need for any central coordinators of the network; (ii) the computational load imposed on each cell is kept to a minimum; and, (iii) required message exchanges via backhaul result in only small levels of overhead on the network. The simulation results verify that the proposed algorithm finds an efficient JP-CoMP clustering that outperforms previous algorithms in terms of both the sum throughput and edge user throughput. Moreover, the convergence properties and the computational complexity of the proposed algorithm are compared with those of previous algorithms, confirming its usefulness in practical implementations.

Distributed Cell Clustering Based on Multi-Layer Message Passing for Downlink Joint Processing Coordinated Multipoint Transmission