Joint Beamforming and Position Optimization for Fluid RIS-aided ISAC Systems

Fuente: arXiv
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Hauptverfasser: Ye, Junjie, Zhang, Peichang, Li, Xiao-Peng, Huang, Lei, Liu, Yuanwei
Format: Preprint
Veröffentlicht: 2025
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_version_ 1866912805370724352
author Ye, Junjie
Zhang, Peichang
Li, Xiao-Peng
Huang, Lei
Liu, Yuanwei
author_facet Ye, Junjie
Zhang, Peichang
Li, Xiao-Peng
Huang, Lei
Liu, Yuanwei
contents A fluid reconfigurable intelligent surface (fRIS)-aided integrated sensing and communication (ISAC) system is proposed to enhance multi-target sensing and multi-user communication. Unlike the conventional RIS, the fRIS employs movable elements with adjustable positions, offering additional spatial degrees of freedom. In this system, a joint optimization problem is formulated to minimize sensing beampattern mismatch and symbol estimation error. An algorithm based on alternating minimization is devised to handle the resultant non-convex problem, where the subproblems are solved via augmented Lagrangian method, quadratic programming, semidefinite relaxation, and majorization-minimization. A key challenge is that the element positions affect both incident and reflective channels, leading to the high-order composite objective functions. As a remedy, the high-order terms are transformed into linear and linear-difference forms by exploiting the structural characteristics of fRIS and the channels. Numerical results demonstrate the superiority of the proposed scheme over conventional RIS-aided ISAC and other benchmarks.
format Preprint
id arxiv_https___arxiv_org_abs_2501_13339
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Joint Beamforming and Position Optimization for Fluid RIS-aided ISAC Systems
Ye, Junjie
Zhang, Peichang
Li, Xiao-Peng
Huang, Lei
Liu, Yuanwei
Signal Processing
A fluid reconfigurable intelligent surface (fRIS)-aided integrated sensing and communication (ISAC) system is proposed to enhance multi-target sensing and multi-user communication. Unlike the conventional RIS, the fRIS employs movable elements with adjustable positions, offering additional spatial degrees of freedom. In this system, a joint optimization problem is formulated to minimize sensing beampattern mismatch and symbol estimation error. An algorithm based on alternating minimization is devised to handle the resultant non-convex problem, where the subproblems are solved via augmented Lagrangian method, quadratic programming, semidefinite relaxation, and majorization-minimization. A key challenge is that the element positions affect both incident and reflective channels, leading to the high-order composite objective functions. As a remedy, the high-order terms are transformed into linear and linear-difference forms by exploiting the structural characteristics of fRIS and the channels. Numerical results demonstrate the superiority of the proposed scheme over conventional RIS-aided ISAC and other benchmarks.
title Joint Beamforming and Position Optimization for Fluid RIS-aided ISAC Systems
topic Signal Processing
url https://arxiv.org/abs/2501.13339