Joint base station selection and beamforming in uplink SIMO networks with per-user power constraints

Consider an uplink SIMO network consisting of multiple base stations (BSs) and multiple users, where each user has an individual transmit power constraint, and the BSs are allowed to cooperate in data receiving. To guarantee fairness among users and avoid heavy burden of backhaul data exchange, we maximize the minimum S-INR based on joint BS selection and beamforming. We formulate this problem from the perspective of sparse beamforming. However, the scaling ambiguity of the receive beamformers will make the sparse constraints trivial. Inspired by the observation that the transmit beamformer is immune to the scaling ambiguity, we apply the duality theorem to the uplink max-min problem under per-user power constraints, and reformulate it as an equivalent downlink problem. An iterative two-stage algorithm is then developed to solve the sparse beamforming problem efficiently. The effectiveness of the proposed algorithm is demonstrated by numerical simulations.