Robust AN-Aided Beamforming Design for Secure MISO Cognitive Radio Based on a Practical Nonlinear EH Model

Abstract

Energy harvesting techniques are promising in next generation wireless communication systems. However, most of the existing works are based on an ideal linear energy harvesting model. In this paper, a multiple-input single-output cognitive radio network is studied under a practical non-linear energy harvesting model. In order to improve the security of both the primary network and the secondary network, a cooperative jamming scheme is proposed. A robust artificial noise aided beamforming design problem is formulated under the bounded channel state information error model. The formulated problem is non-convex and challenging to be solved. Using ${\mathcal{ S}}\text {-Procedure} $ and the semidefinite relaxation method, a suboptimal beamforming can be obtained. Simulation results show that the performance achieved under the non-linear energy harvesting model may be better than that obtained under the linear energy harvesting model. It is also shown that the cooperation between the primary network and the secondary network can obtain a performance gain compared with that without this cooperation.