Robust adaptive beamforming against large steering vector mismatch based on minimum dispersion Abstract   Many efforts have been recently devoted to adaptive beamformers based on the minimum dispersion (MD) criterion for nonGaussian signals, which results in improved signaltonoise ratio performance. However, large steering vector mismatch and inappropriate choice of uncertainty set will cause performance degradation to the existing MDbased methods. To address these issues, we develop a robust MDbased beamformer against large steering vector mismatch, which utilizes multiple small uncertainty sets to cover the whole uncertainty region. The      l    p    xe2x88x92   norm     (   p  xe2x89xa5  1   ) minimization problem turns to be nonlinear and nonconvex because of these multiuncertaintyset constraints. To solve the problem, a projected gradient algorithm is utilized to transform the original problem into a nonconvex quadratically constrained quadratic programming (QCQP) problem. The semidefinite programming relaxation technique is then employed in each iteration to deal with the nonconvex QCQP problem. Numerical results demonstrate that the proposed beamformer offers a significant performance improvement in case of large steering vector mismatch for nonGaussian signals compared with the conventional schemes.

A WorstCase Performance Optimization Based Design Approach to Robust SymbolLevel Precoding for Downlink MUMIMO This paper addresses the optimization problem of symbollevel precoding (SLP) in the downlink of a multiuser multipleinput multipleoutput (MUMIMO) wireless system while the precoderxe2x80x99s output is subject to partiallyknown distortions. In particular, we assume a linear distortion model with bounded additive noise. The original signaltointerferenceplusnoise ratio (SINR) constrained SLP problem minimizing the total transmit power is first reformulated as a penalized unconstrained problem, which is referred to as the relaxed robust formulation. We then adopt a worstcase design approach to protect the usersxe2x80x99 intended symbols and the targeted constructive interference with a desired level of confidence. Due to the nonconvexity of the relaxed robust formulation, we propose an iterative algorithm based on the block coordinate ascentdescent method. We show through simulation results that the proposed robust design is flexible in the sense that the CI constraints can be relaxed so as to keep a desirable balance between achievable rate and power consumption. Remarkably, the new formulation yields more energyefficient solutions for appropriate choices of the penalty parameter, compared to the original SLP problem.