Fluid Reconfigurable Intelligent Surface (FRIS) Enabling Secure Wireless Communications

TL;DR

This work addresses securing wireless communications by leveraging fluid RIS (FRIS), a positioning-reconfigurable extension of RIS. The authors formulate a secrecy-rate maximization problem in a MISO setup and solve it with an alternating-optimization framework, where transmit beamforming is obtained from a closed-form generalized eigenvalue solution and FRIS configuration is optimized via cross-entropy optimization. The approach jointly optimizes the AP beamformer, FRIS active-element subset, and discrete phase shifts, demonstrating substantial secrecy-rate gains over conventional RIS and baselines in simulations. The results illustrate that the positioning flexibility of FRIS provides a significant security advantage, with performance improving as the number of candidate locations (N) or activated elements (hatN) increases, and showing resilience to eavesdropper position variations.

Abstract

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).

Figures (5)

• Figure 1: A FRIS-assisted secure communication system.
• Figure 2: Average secrecy rate vs. AP transmit power ($\hat{N}=16$).
• Figure 3: Average secrecy rates vs. number of activated elements.
• Figure 4: Average secrecy rate vs. total available locations $N$ ($\hat{N}=16$).
• Figure 5: Average secrecy rate vs. eavesdropper's location ($\hat{N}=16$).