Performance Analysis and Optimization of IRS-Aided Covert Communication With Hardware Impairments
Chunqi Chen, Manlin Wang, Bin Xia, Yinghong Guo, Jiangzhou Wang
Abstract
Residual hardware impairments widely exist in transceivers and intelligent reflecting surface (IRS) in practical systems, which lead to serious signal distortion, causing performance loss and covert transmission challenging. In this paper, we study the robust transmission design for an IRS-aided covert communication system in the presence of transceiver and IRS hardware impairments. To maximize the signal-to-noise ratio at the legitimate receiver and satisfy the covertness requirement, the transmit power at the source and the reflection coefficients at the IRS are jointly optimized. Since the optimization variables are coupled, an alternating optimization algorithm is proposed to solve the optimization problem. Specifically, in each iteration, the analytical expression of the optimal transmit power is obtained, and the penalty successive convex approximation algorithm is adopted to obtain the optimal reflection coefficients. Numerical results show the performance loss caused by hardware impairments. Besides, by comparing the values of Kullback-Leibler divergence, results also illustrate that the proposed transmission scheme is more robust to the hardware impairments, as the nonrobust designed parameters can not satisfy the covert constraint.