Robust receive beamforming with interference and channel uncertainty

In this paper, we introduce a general convex framework for robust beamforming, which is valid for both deterministic and stochastic uncertainty models, and provides robustness against errors both in the channel and in the interference co-variance matrix estimations. Furthermore, we extend our design to a multiple-state interference model and show the performance gains obtained by exploiting the interference structure.