Securing Intelligent Reflecting Surface Assisted Terahertz Systems
KAUST DepartmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Electrical and Computer Engineering Program
Permanent link to this recordhttp://hdl.handle.net/10754/676669
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AbstractThis paper focuses on securing confidential communication in multiple intelligent reflecting surfaces (IRS) assisted terahertz (THz) systems, where a potential eavesdropper can intercept either the base station (BS)-IRS link or the IRS-user link. Notably, the secure transmission may be intercepted and blocked by the eavesdropper due to the blockage-prone nature in THz bands. To characterize the blocking effects of the eavesdropper, the blocking-based path loss is first investigated. With the imperfect eavesdropper channel state information (ECSI), the worst-case secrecy rate (WCSR) is derived, and a joint optimization problem of hybrid beamforming at the BS and reflecting beamforming at the IRS is formulated. For the BS-IRS link eavesdropping, the zero-forcing (ZF) principle-based hybrid beamforming and the closed-form phase shifts of multiple IRSs are respectively proposed. For the IRS-user link eavesdropping, an iterative algorithm is proposed to tackle the non-convex optimization problem with a given information leakage threshold. Finally, a robust secure transmission strategy for multi-eavesdropper systems is further investigated. Simulation results demonstrate that compared with blockage-unaware scenarios, our proposed scheme can resist the adverse effects of the blockage-prone nature of THz waves on information security, and significantly boost secrecy performance.
CitationQiao, J., Zhang, C., Dong, A., Bian, J., & Alouini, M.-S. (2022). Securing Intelligent Reflecting Surface Assisted Terahertz Systems. IEEE Transactions on Vehicular Technology, 1–1. https://doi.org/10.1109/tvt.2022.3172763
SponsorsSupported in part by the National Natural Science Foundation of China (No. 61901247, 61701269, 62101311), and Natural Science Foundation of Shandong Province of China (No. ZR2019BF032, ZR2020QF001), and the KAUST Office of Sponsored Research.
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