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We study the problem of interference management in large-scale small cellnetworks, where each user equipment (UE) needs to determine in a distributedmanner when and at what power level it should transmit to its serving smallcell base station (SBS) such that a given network performance criterion ismaximized subject to minimum quality of service (QoS) requirements by the UEs.We first propose a distributed algorithm for the UE-SBS pairs to find a subsetof weakly interfering UE-SBS pairs, namely the maximal independent sets (MISs)of the interference graph in logarithmic time (with respect to the number ofUEs). Then we propose a novel problem formulation which enables UE-SBS pairs todetermine the optimal fractions of time occupied by each MIS in a distributedmanner. We analytically bound the performance of our distributed policy interms of the competitive ratio with respect to the optimal network performance,which is obtained in a centralized manner with NP (non-deterministic polynomialtime) complexity. Remarkably, the competitive ratio is independent of thenetwork size, which guarantees scalability in terms of performance forarbitrarily large networks. Through simulations, we show that our proposedpolicies achieve significant performance improvements (from 150% to 700%) overthe existing policies.

Distributed Interference Management Policies for Heterogeneous Small Cell Networks