Worst-case weighted sum-rate maximization for MISO downlink systems with imperfect channel knowledge

Abstract

We consider the worst-case weighted sum-rate maximization (WSRMax) problem under imperfect channel state information (CSI) in multicell downlink multiple-input singleoutput systems. The problem is known to be NP-hard even for the perfect CSI case. We propose a solution method, based on semi-definite relaxation (SDR) and branch and bound technique, which solves globally the noncovex robust WSRMax problem with an optimality certificate. Novel bounding technique based on SDR is proposed.Index Terms-Branch and bound, weighted sum-rate maximization, semi-definite programming, multicell networks, robust design.