Multi-Functional RIS Integrated Sensing and Communications for 6G Networks

TL;DR

This paper introduces a multi-functional reconfigurable intelligent surface (MF-RIS) that enhances integrated sensing and communication systems by supporting reflection, refraction, amplification, and sensing, with optimized configurations for multi-user and multi-target scenarios.

Contribution

The paper proposes a novel MF-RIS design supporting multiple functions and develops an optimization framework for joint beamforming and RIS configuration in multi-user, multi-target ISAC systems.

Findings

MF-RIS with energy splitting protocol outperforms other RIS types.

Proposed MF-RIS achieves significant sensing SINR gains over passive and active RIS.

Sensing performance saturates beyond a certain number of sensing elements.

Abstract

In this paper, we propose a novel multi-functional reconfigurable intelligent surface (MF-RIS) that supports signal reflection, refraction, amplification, and target sensing simultaneously. Our MF-RIS aims to enhance integrated communication and sensing (ISAC) systems, particularly in multi-user and multi-target scenarios. Equipped with reflection and refraction components (i.e., amplifiers and phase shifters), MF-RIS is able to adjust the amplitude and phase shift of both communication and sensing signals on demand. Additionally, with the assistance of sensing elements, MF-RIS is capable of capturing the echo signals from multiple targets, thereby mitigating the signal attenuation typically associated with multi-hop links. We propose a MF-RIS-enabled multi-user and multi-target ISAC system, and formulate an optimization problem to maximize the signal-to-interference-plus-noise ratio (SINR) of sensing targets. This problem involves jointly optimizing the transmit beamforming and MF-RIS configurations, subject to constraints on the communication rate, total power budget, and MF-RIS coefficients. We decompose the formulated non-convex problem into three sub-problems, and then solve them via an efficient iterative algorithm. Simulation results demonstrate that: 1) The performance of MF-RIS varies under different operating protocols, and energy splitting (ES) exhibits the best performance in the considered MF-RIS-enabled multi-user multi-target ISAC system; 2) Under the same total power budget, the proposed MF-RIS with ES protocol attains 52.2%, 73.5% and 60.86% sensing SINR gains over active RIS, passive RIS, and simultaneously transmitting and reflecting RIS (STAR-RIS), respectively; 3) The number of sensing elements will no longer improve sensing performance after exceeding a certain number.