Outage Constrained Secure Beamforming for IRS-Assisted Cognitive Radio Networks

This paper proposes a secure beamforming scheme to enhance the physical layer security (PLS) in the intelligent reflecting surface (IRS) assisted cognitive radio networks (CRNs). Taking the statistical channel state information (CSI) error of eavesdroppers (Eves) related channels into account, we jointly optimize the transmit beamforming at the cognitive base station (CBS) and reflect beamforming at the IRS to minimize the transmit power subject to the quality of service of secondary user (SU), the limited interference on the primary users (PUs), the secrecy rate (SR) outage probability constraint of SU and unit modulus of the IRS. To tackle this mathematically intractable problem, we first transform the non-convex outage constraint into deterministic form by using the Bernstein-type inequality and then exploit the alternating optimization method with the help of semi-definite relaxation (SDR) and Gaussian randomization method. Simulation results show that our proposed algorithm can significantly reduce the transmit power compared with that without IRS, and allows us to use fewer antenna number of CBS.