Secrecy Energy Efficiency Maximization in IRS-Assisted Cognitive Radio System

This letter investigated the application of intelligent reflecting surface (IRS) in an underlay cognitive radio network, in which a secrecy energy efficiency (SEE) optimization beamforming design is proposed to achieve a trade-off between energy efficiency and physical layer security. Specifically, optimal transmitter and IRS beamformers are formulated to maximize the SEE under the premise that certain secrecy rate of secondary user and power of cognitive transmission are ensured, and the leakage interference to primary user restricted under a predefined threshold. Based on the Dinkelbach's method, we propose an iterative optimization algorithm to jointly design the transmit and reflect beamforming at the transmitter and IRS, respectively. Furthermore, a second-order-cone-programming approximation approach is developed to reduce the computational complexity. Numerical results are provided to demonstrate the effectiveness of our proposed algorithm.