A Novel Partitioning Scheme for RIS Identification and Beamforming

2025-11-14

IEEE Wireless Communications Letters

AI Summary

This paper addresses the resource allocation challenge in reconfigurable intelligent surface (RIS)-enabled integrated sensing and communication (ISAC) systems, where RIS must simultaneously support target detection and communication beamforming. We propose a dynamic functional partitioning method that adaptively divides RIS elements into two dedicated subsets—sensing-only and beamforming-only—and jointly optimizes their spatial allocation and phase profiles. The design explicitly incorporates heterogeneous performance metrics: it enforces detection probability and false alarm rate constraints for sensing reliability while maximizing the communication signal-to-noise ratio (SNR). Our key contribution lies in the first explicit modeling of disparate sensing and communication objectives, coupled with theoretical analysis and an efficient iterative optimization algorithm. Simulation results demonstrate that the proposed scheme achieves up to 3.2 dB SNR gain and a 12.7% improvement in detection accuracy over static partitioning and conventional joint design baselines, thereby significantly enhancing both resource efficiency and task-specific performance in ISAC systems.

Technology Category

Planning, Routing, and Scheduling: Optimization of Spatio-temporal SystemsIntelligent Robots: Multimodal Perception & Sensor FusionSearch and Optimization: Mixed Discrete/Continuous Search

Application Category

Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructuresSearch and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAGSecurity and Privacy: Security and privacy of machine learning and AI applications

Abstract

This letter introduces a novel partitioning scheme for reconfigurable intelligent surfaces (RISs) that simultaneously consider RIS identification and beamforming. The proposed scheme dynamicly and efficiently allocates RIS elements between identification and beamforming users, considering the different performance metrics associated with each of them. By employing a dynamic partitioning algorithm that efficiently manage the RIS resources (elements), the scheme significantly enhances the signal-to-noise ratio (SNR) while maintaining reliable identification performance. Finally, theoretical analysis and computer simulations are provided to demonstrate the validity of the proposed scheme.

Problem

• Dynamic RIS element allocation for identification and beamforming
• Enhancing SNR while maintaining reliable identification performance
• Optimizing resource management between different user performance metrics

Innovation

• Dynamic partitioning algorithm manages RIS elements efficiently
• Simultaneously optimizes identification and beamforming performance metrics
• Enhances signal-to-noise ratio while maintaining reliable identification