AN-Aided Transmit Beamforming Design for Secured Cognitive Radio Networks with SWIPT

Abstract

We investigate multiple-input single-output secured cognitive radio networks relying on simultaneous wireless information and power transfer (SWIPT), where a multiantenna secondary transmitter sends confidential information to multiple single-antenna secondary users (SUs) in the presence of multiple single-antenna primary users (PUs) and multiple energy-harvesting receivers (ERs). In order to improve the security of secondary networks, we use the artificial noise (AN) to mask the transmit beamforming. Optimization design of AN-aided transmit beamforming is studied, where the transmit power of the information signal is minimized subject to the secrecy rate constraint, the harvested energy constraint, and the total transmit power. Based on a successive convex approximation (SCA) method, we propose an iterative algorithm which reformulates the original problem as a convex problem under the perfect channel state information (CSI) case. Also, we give the convergence of the SCA-based iterative algorithm. In addition, we extend the original problem to the imperfect CSI case with deterministic channel uncertainties. Then, we study the robust design problem for the case with norm-bounded channel errors. Also, a robust SCA-based iterative algorithm is proposed by adopting the $\mathcal{S}$-Procedure. Simulation results are presented to validate the performance of the proposed algorithms.