Efficient Heuristics for Clustering and Power Allocation in Small Cell Networks

Heterogeneous and small cell networks (HetSNets) have emerged as a promising mean to significantly improve coverage and performance of next generation cellular networks. However, the high density of base stations in such networks accentuates the harmful impact of interference on network performance. This paper considers a network of multiple small cells where the base stations seek to maximize a common objective by forming clusters and allocating power to their users. We formulate the joint clustering and power allocation problem as a mixed integer optimization problem. We show that such problems can be optimally solved only by performing an exhaustive search over all the possible clustering decisions. Furthermore, it is shown that even if the clustering is established the power allocation problem remains NP-hard. Due to the high computational complexity of the optimal solution, we propose three heuristic algorithms which perform greedy clustering and iterative power allocation. Simulations show that the proposed algorithms, and especially the neighboring links first heuristic, provide a good computational complexity/performance tradeoff.