Beamforming Optimization for Extremely Large-Scale RIS-Aided Near-Field Secure Communications
This work addresses physical layer security for near-field communications using XL-RIS, which is an incremental improvement in a domain-specific area of wireless communication.
The paper tackled secure communication in extremely large-scale RIS-aided near-field systems by jointly optimizing beamforming and RIS reflection coefficients, introducing artificial jamming to enhance security, and demonstrated through simulations that the scheme ensures secure communication even when an eavesdropper is in the same direction and closer to the RIS than the legitimate user.
This paper studies an extremely large-scale reconfigurable intelligent surface (XL-RIS)-aided near-field physical layer security (PLS) communication system, aiming to maximize the secrecy rate by jointly optimizing precoding vector at the BS and the reflection coefficient matrix at the XL-RIS. Artifi-cial jamming was introduced to further enhance communication security. To solve the non-convex secrecy rate problem, an alternate optimization-based algorithm is adopted to decompose it into two sub-problems. Specifically, when optimizing the transmit beamformer at the BS, the non-convex prob-lem is transformed into a convex one through the weighted minimum mean-square error and the successive convex approximation-based algorithms. For the optimization problem of the XL-RIS phase-shifting matrix, a low-complexity alternating direction method of multipliers-based algorithm is employed to enhance the flexibility of the design. The proposed algorithm is capable of accommodating discrete phase optimization for the XL-RIS, thus better aligning with practical system requirements. Simulation results demonstrate that when the eavesdropper reside in the same direction as the legitimate user and is located closer to the XL-RIS, the proposed scheme in this paper can still ensure the secure communication.