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Decentralized User Scheduling and Beamforming in Multi-cell MIMO Networks

We study the problem of distributed user scheduling and beamforming in multi-user, multi-cell, multiple-input multiple-output (MIMO) networks to maximize the weighted sum-rate. While previous work has focused on optimizing the signal-to-leakage-plus noise ratio (SLNR) or the signal-to-interference-plus-noise ratio (SINR), we propose a new signal-to-leakage-plus-interference-plus-noise ratio (SLINR) metric which hybridizes the SINR and SLNR by incorporating the intra-cell interference and inter-cell leakage. Using fractional programming and the Hungarian algorithm, we construct an iterative resource allocator that performs user scheduling and beamforming while accounting for channel estimation errors. Furthermore, we show different approaches for calculating the leakage which vary in terms of practicality and scalability. These approaches decrease the complexity compared to the standard method of leakage calculation, while providing comparable performance. Our results show that resource allocation based on the SLINR metric is a promising solution for decentralized implementation.