Self-Sustainable IRS Assisted Covert Communications: Analysis and Optimization
Manlin Wang, Chunqi Chen, Xing Lv, Bin Xia · 2024
The intelligent reflecting surface (IRS) has been widely applied to establish an environment suitable for covert communications, which hides the existence of transmission behavior. Unfortunately, the existing IRS usually relies on battery/grid power supply for its operations, which limits its performance and is even unprocurable in covert communications. To address the above dilemma, a self-sustainable IRS with active reflection elements is considered in this paper to facilitate covert communications, where the IRS is powered by wireless energy harvesting (EH) from the incident signals. To reveal the benefits brought by the self-sustainable IRS for covert communications, the covert rate and the detection error probability at the warder are derived to evaluate the transmission effectiveness and covertness. Besides, the covert rate maximization problem is formulated by jointly optimizing beamforming vectors, jamming power, EH-related factor and reflection coefficient matrix. Further, to solve this non-convex problem, an alternating optimization-based algorithm is proposed by exploiting semidefinite programming and successive convex approximation techniques. Simulation results demonstrate the superiority of the proposed scheme compared with the existing benchmarks, where energy self-sustainability and multiplicative-fading mitigation are achieved by the self-sustainable IRS. In addition, a non-trivial tradeoff exists between covert rates and self-sustainability, providing insights into the optimal number of reflection elements and the deployment position of the IRS.