Worst-Case Weighted Sum-Rate Maximization for MISO Downlink Systems via Branch and Bound
نویسندگان
چکیده
We consider the worst-case weighted sum-rate maximization (WSRMax) problem under imperfect channel state information in multicell downlink multi-input single-output systems. The problem is known to be NP-hard. We propose a solution method, based on semi-definite relaxation and branch and bound technique, which solves globally the noncovex robust WSRMax problem with an optimality certificate. The proposed method can be easily extended to maximize any worst-case system performance metric that is Lipschitz continuous and increasing function of signal-to-interference-plus-noise ratio.
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تاریخ انتشار 2013