MIMO IBC beamforming with combined channel estimate and covariance CSIT

Tabikh, Wassim; Slock, Dirk TM; Yuan-Wu, Yi
ISIT 2017, IEEE International Symposium on Information Theory June 25-30, 2017, Aachen, Germany

This work deals with beamforming for the MIMO Interfering Broadcast Channel (IBC), i.e. the Multi-Input Multi-Output (MIMO) 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. We introduce the first large system analysis for optimized beamformers with partial CSIT, here for the Massive MISO (MaMISO) case. 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.

DOI
Type:
Conférence
City:
Aachen
Date:
2017-06-25
Department:
Systèmes de Communication
Eurecom Ref:
5215
Copyright:
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