Downlink beamforming optimization for cognitive underlay networks

Abstract

Cognitive radio (CR) is an advanced enabling technology for improving the spectrum utilization in wireless systems. Specially, spectrum underlay systems assign licensed bandwidth to a secondary network while guaranteeing the quality of service (QoS) for a primary network. In this paper, we consider downlink CR underlay multiple-input single-output (MISO) networks comprising primary and secondary transmitters serving multiple user. In particular, we formulate the following beamforming optimization problems: 1) total transmit power minimization problem; 2) mean-square error balancing problem; and 3) network interference power minimization problem. In the presence of perfect channel state information (CSI), we formulate the optimization algorithms in a centralized manner and determine the optimal beamformers using standard convex optimization techniques. To account imperfect CSI, we also propose robust algorithms through the worst-case design to mitigate the effect of channel uncertainty. Finally, numerical results are provided to illustrate the validity of our proposed algorithms.