Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces
Xianghao Yu, Dongfang Xu, Ying Sun, Derrick Wing Kwan Ng, and Robert, Schober

TL;DR
This paper proposes a robust optimization framework using intelligent reflecting surfaces (IRSs) to enhance physical layer security in wireless systems with imperfect channel knowledge, demonstrating significant secrecy improvements.
Contribution
It introduces a joint design of beamformers, artificial noise, and IRS phase shifts under imperfect CSI, with an efficient algorithm for maximizing system sum-rate while ensuring security.
Findings
IRSs significantly improve secrecy performance.
Distributed IRS deployment outperforms single IRS configurations.
The proposed algorithm effectively handles non-convex optimization problems.
Abstract
In this paper, intelligent reflecting surfaces (IRSs) are employed to enhance the physical layer security in a challenging radio environment. In particular, a multi-antenna access point (AP) has to serve multiple single-antenna legitimate users, which do not have line-of-sight communication links, in the presence of multiple multi-antenna potential eavesdroppers whose channel state information (CSI) is not perfectly known. Artificial noise (AN) is transmitted from the AP to deliberately impair the eavesdropping channels for security provisioning. We investigate the joint design of the beamformers and AN covariance matrix at the AP and the phase shifters at the IRSs for maximization of the system sum-rate while limiting the maximum information leakage to the potential eavesdroppers. To this end, we formulate a robust nonconvex optimization problem taking into account the impact of the…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Wireless Communication Security Techniques · Ocular Disorders and Treatments
