Robust Downlink Beamforming for Cognitive Radio Networks

We address the problem of worst-case robust downlink beamforming for a multi-antenna secondary network (SN) in a cognitive radio framework. An important issue is the interference leaked to the primary users (PUs) resulting from the transmission between the SN base station and the secondary users (SUs). Our aim is to provide the SUs with a minimum acceptable quality-of-service (QoS), while keeping the interference to the PUs below a given threshold. Previous solutions for this scenario involve several coarse approximations. Here we avoid these approximations and obtain an exact reformulation of the worst-case problem using Lagrange duality. Finally, we use semidefinite relaxation (SDR) to convert the resulting problem to a convex form. Computer simulations show that the SDR step does not involve any approximation as the resulting solution is always rank-one.