Robust adaptive beamforming for general-rank signal models

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Distributed Beamforming for Relay Networks Based on Second-Order Statistics of the Channel State Information (2008, methodology): “To cope with such performance degradation, one has to resort to robust techniques proposed in [23], where positive and negative diagonal loading techniques are used to compensate for the lack of the precise knowledge of the correlation matrices.”
A robust maximin approach for MIMO communications with imperfect channel state information based on convex optimization (2006, background): “This was afterwards generalized in [30] to embrace uncertainties both in the array response and the covariance matrix.”
Principles of minimum variance robust adaptive beamforming design (2013, methodology): “In order to provide robustness against the normbounded mismatches JD1JrE and JD2Jrg (where E and g are some preselected bounds) in the desired signal and data sample covariance matrices, respectively, the worstcase optimization-based MVDR RAB design principle has been extended and the following solu”