Maximizing Sum-Rate Performance in Constrained Multicell Networks with Limited Information Exchange

A deep reinforcement learning-based approach is proposed to maximize the sum-rate performance in multicell networks with limited backhaul capacity and a small number of antennas per base station, by efficiently designing the beamforming vectors with minimal information exchange between base stations.