Base Station Selection for Massive MIMO Networks With Two-Stage Precoding

Two-stage precoding has been proposed to reduce the overhead of both the channel training and the channel state information feedback in massive multiple-input multiple-output systems. But the overlap of the angle-spreading-ranges (ASR) for different user clusters may seriously degrade the performance of two-stage precoding. In this letter, we propose an ASR overlap mitigating scheme through the base station (BS) selection. First, the BS selection is formulated as a sum signal-to-interference-plus-noise ratio maximization problem. Then, the problem is solved by a low-complex algorithm through maximizing the signal-to-leakage-plus-noise ratio (SLNR). In addition, we propose a low-overhead algorithm with the lower bound on the average SLNR as the objective function. Finally, we demonstrate the efficacy of the proposed schemes through numerical simulations.