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Multicell coordinated beamforming (MCBF) has been recognized as a promisingapproach to enhancing the system throughput and spectrum efficiency of wirelesscellular systems. In contrast to the conventional single-cell beamforming (SBF)design, MCBF jointly optimizes the beamforming vectors of cooperative basestations (BSs) (via a central processing unit(CPU)) in order to mitigate theintercell interference. While most of the existing designs assume that the CPUhas the perfect knowledge of the channel state information (CSI) of mobilestations (MSs), this paper takes into account the inevitable CSI errors at theCPU, and study the robust MCBF design problem. Specifically, we consider theworst-case robust design formulation that minimizes the weighted sumtransmission power of BSs subject to worst-casesignal-to-interference-plus-noise ratio (SINR) constraints on MSs. Theassociated optimization problem is challenging because it involves infinitelymany nonconvex SINR constraints. In this paper, we show that the worst-caseSINR constraints can be reformulated as linear matrix inequalities, and theapproximation method known as semidefinite relation can be used to efficientlyhandle the worst-case robust MCBF problem. Simulation results show that theproposed robustMCBF design can provide guaranteed SINR performance for the MSsand outperforms the robust SBF design.

Worst-Case SINR Constrained Robust Coordinated Beamforming for Multicell Wireless Systems