Secure Resource Allocation for IRS-Assisted CRNs Under Opportunistic Spectrum Access

In this paper, an intelligent reflecting surface (IRS)-assisted secure cognitive radio networks (CRNs) is investigated under the opportunistic spectrum access (OSA) mode. The imperfect channel state information (CSI) of primary links and eavesdropping links are considered. The aim is to maximize the sum secrecy rate of the secondary user receivers (SU-RXs) by jointly optimizing the sensing time, the beamforming design of the secondary base station (SBS) and the phase shifts of IRS. An iterative block coordinate descent (BCD)-based algorithm with successive convex approximation (SCA) and semidefinite relaxation (SDR) is exploited to solve the non-convex problem. Moreover, a safe approximation is adopted to transform the $Q-\mathbf{function}$ into a tractable expression. Furthermore, the $\mathcal{S}-\mathbf{procedure}$ is adopted to tackle the imperfect CSI. Simulation results show that the proposed scheme can greatly improve the secrecy performance of CRNs.