The concept of fluid reconfigurable intelligent surface (FRIS) upgrades the conventional reconfigurable intelligent surface (RIS) paradigm by empowering its reflecting elements with positioning reconfigurability. This letter aims to investigate the use of FRIS to enhance physical-layer security in a system, in which a multi-antenna access point (AP) communicates with a legitimate user device in the presence of an eavesdropper. Unlike RIS with fixed-position elements, FRIS can dynamically select an optimal subset of elements from a larger array of candidate locations. We aim to maximize the secrecy rate by jointly optimizing the AP's transmit beamforming, the selection of FRIS activated elements, and their discrete phase shifts. The resulting problem is a challenging mixed-integer nonlinear program (MINLP), which is NP-hard. To address this, we propose an efficient algorithm based on an alternating optimization (AO) framework. Within this framework, the beamforming subproblem is optimally solved in closed form using the generalized eigenvalue method, while the combinatorial subproblem of joint element selection and discrete phase design is handled via the cross-entropy optimization (CEO) method. Simulation results show that the proposed FRIS design significantly outperforms the conventional RIS counterpart and other baselines, demonstrating the substantial security gains by element positioning as the new degree of freedom (DoF).
翻译:流体可重构智能表面(FRIS)的概念通过赋予反射元件位置可重构性,升级了传统可重构智能表面(RIS)的范式。本文旨在研究利用FRIS增强物理层安全性,该系统包含一个多天线接入点(AP)在窃听者存在的情况下与合法用户设备通信。与具有固定位置元件的RIS不同,FRIS能够从更大的候选位置阵列中动态选择最优元件子集。我们旨在通过联合优化AP的发射波束成形、FRIS激活元件的选择及其离散相位偏移,最大化保密速率。该问题是一个具有挑战性的混合整数非线性规划(MINLP),属于NP难问题。为解决此问题,我们提出了一种基于交替优化(AO)框架的高效算法。在该框架内,波束成形子问题通过广义特征值方法以闭式形式最优求解,而联合元件选择与离散相位设计的组合子问题则通过交叉熵优化(CEO)方法处理。仿真结果表明,所提出的FRIS设计显著优于传统RIS方案及其他基线方法,证明了元件位置作为新自由度(DoF)所带来的显著安全增益。