MaMISO IBC beamforming design with combined channel estimate and covariance CSIT: A large system analysis

This work deals with beamforming for the MaMISO Interfering Broadcast Channel (IBC), i.e. the Massive Multi-Input Single-Output (MaMISO) Multi-User Multi-Cell downlink (DL). The novel beamformers are here optimized for the Expected Weighted Sum Rate (EWSR) for the case of Partial Channel State Information at the Transmitters (CSIT). Gaussian partial CSIT can optimally combine channel estimate and channel covariance information. We introduce the first large system analysis for optimized beamformers with partial CSIT. In the case of Gaussian partial CSIT, the beamformers only depend on the means and covariances of the channels. The large system analysis furthermore allows to predict the EWSR performance on the basis of the channel statistics only.