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Partially connected hybrid beamforming (HBF) is a promising approach to alleviate the implementation of large scale millimeter-wave multiple-input multiple-output (MIMO) systems. In this paper, we develop rate maximizing algorithms for the full array- and subarray-based processing strategies of partially connected HBF. We formulate the rate maximization problem as a weighted mean square error minimization problem and use alternating optimization to tackle it.

In this paper, we propose a robust analog-only beamforming scheme for the downlink multi-user systems, which not only suppresses the interference and enhances the beamform- ing gain, but also provides robustness against imperfect channel state information (CSI). We strike a balance between the average beamforming gain and the inter-user interference by formulating a multi-objective problem. A probabilistic objective of leakage interference power is formulated to alleviate the effects of the channel estimation and feedback quantization errors.