Robust downlink beamforming in multiuser MISO Cognitive Radio Networks

This paper is concerned with robust downlink beamforming in a multiuser Multi-Input Single-Output (MISO) Cognitive Radio Network (CR-Net) in which multiple Primary Users (PUs) coexist with multiple Secondary Users (SUs). It is assumed that the Channel State Information (CSI) for all relevant channels is not perfectly known. We design the linear precoder matrix to minimize the transmit power of the SU-Transmitter (SU-Tx) and simultaneously targeting a lower bound on the received Signal-to-Interference-plus-Noise-Ratio (SINR) for the SU's, while requiring an upper bound on the Interference-Power (IP) at the PUs. The method used is based on a worst case design scenario through which the performance metrics of the design are immune to variations of the channels. Three approaches based on convex programming are proposed. Finally, simulation results are provided to evaluate the robustness of the proposed approaches.