Massive MISO IBC beamforming - A multi-antenna stochastic geometry perspective

Kurisummoottil Thomas, Christo; Slock, Dirk TM
GLOBECOM 2018, IEEE Workshop on Emerging Technologies for 5G and Beyond Wireless and Mobile Networks, 9-13 December 2018, Abu Dhabi, UAE

This work deals with coordinated beamforming (BF) for the Multi-Input Single-Output (MISO) Interfering Broadcast Channel (IBC), i.e. the MISO 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 (posterior) partial CSIT can optimally combine channel estimate
and channel covariance information. With Gaussian partial CSIT, the beamformers only depend on the means (estimates) and (error) covariances of the channels. We extend a recently introduced large system analysis for optimized beamformers with partial CSIT, by a stochastic geometry inspired randomization of the channel covariance eigen spaces, leading to much simpler analytical results, which depend only on some essential channel
characteristics. In the Massive MISO (MaMISO) limit, we obtain deterministic approximations of the signal and interference plus noise powers at the receivers, which are tight as the number of antennas and number of users M;K ! 1 at fixed ratio. Simulation results exhibit the correctness of the large system results and the performance superiority of optimal BF designs based on both the MaMISO limit of the EWSR and using Linear
Minimum Mean Squared Error (LMMSE) channel estimates.

Abu Dhabi
Communication systems
Eurecom Ref:
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