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.

翻译：本文研究了一种超大规模可重构智能表面辅助的近场物理层安全通信系统，旨在通过联合优化基站处的预编码向量与XL-RIS处的反射系数矩阵，最大化保密速率。系统引入了人工干扰以进一步增强通信安全性。为解决非凸的保密速率最大化问题，采用了一种基于交替优化的算法，将其分解为两个子问题。具体而言，在优化基站处的发射波束成形器时，通过加权最小均方误差和基于逐次凸逼近的算法，将非凸问题转化为凸问题。针对XL-RIS相移矩阵的优化问题，采用了一种基于交替方向乘子法的低复杂度算法，以增强设计的灵活性。所提算法能够适应XL-RIS的离散相位优化，从而更好地符合实际系统需求。仿真结果表明，当窃听者与合法用户处于相同方向且更靠近XL-RIS时，本文所提方案仍能确保安全通信。