Robust resource allocation for IRS‐assisted secure cognitive radio networks

Abstract

Abstract In this paper, a robust resource allocation problem in an intelligent reflecting surface (IRS) assisted artificial noise (AN)‐aided cognitive radio network is investigated. Considering that the channel state information (CSI) of the eavesdropper channel and interference channel cannot be perfectly known in practice, the aim is to minimise the power consumption of the secondary user transmitter (SU‐TX) by jointly optimising the transmit beamforming and covariance matrix of AN at the SU‐TX as well as the phase shifts of the IRS. The formulated problem is non‐convex and challenging to tackle due to the coupling among multiple variables. An efficient alternative optimisation algorithm to solve it by exploiting the S ‐procedure and semi‐definite relaxation. Simulation results demonstrate that the IRS helps in reducing the power consumption significantly even under imperfect CSI conditions.