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Interference alignment (IA) is a promising technique for interferencemitigation in multicell networks due to its ability to completely cancel theintercell interference through linear precoding and receive filtering. In smallnetworks, the amount of required channel state information (CSI) is modest andIA is therefore typically applied jointly over all base stations. In largenetworks, where the channel coherence time is short in comparison to the timeneeded to obtain the required CSI, base station clustering must be appliedhowever. We model such clustered multicell networks as a set of coalitions,where CSI acquisition and IA precoding is performed independently within eachcoalition. We develop a long-term throughput model which includes both CSIacquisition overhead and the level of interference mitigation ability as afunction of the coalition structure. Given the throughput model, we formulate acoalitional game where the involved base stations are the rational players.Allowing for individual deviations by the players, we formulate a distributedcoalition formation algorithm with low complexity and low communicationoverhead that leads to an individually stable coalition structure. The dynamicclustering is performed using only long-term CSI, but we also provide a robustshort-term precoding algorithm which accounts for the intercoalitioninterference when spectrum sharing is applied between coalitions. Numericalsimulations show that the distributed coalition formation is generally able toreach long-term sum throughputs within 10 % of the global optimum.

Distributed Long-Term Base Station Clustering in Cellular Networks using Coalition Formation