Exploring the Near and Far-Field Coexistence for RIS-Assisted ISAC Systems: An Adaptive Bandwidth Splitting Approach

TL;DR

This paper proposes an adaptive bandwidth-splitting approach for RIS-assisted ISAC systems that operate in both near-field and far-field environments, optimizing sensing and communication performance.

Contribution

It introduces a joint optimization framework for bandwidth splitting, beamforming, and RIS phase shifts in NF and FF coexistence scenarios, enhancing ISAC system performance.

Findings

Significant performance improvements over conventional schemes.

Effective handling of NF and FF coexistence in RIS-assisted ISAC.

Optimized resource allocation enhances sensing and communication quality.

Abstract

Integrated sensing and communication (ISAC) enables the joint use of spectrum and hardware resources for radar sensing and data transmission, serving as a key enabler of next-generation wireless networks. However, most existing ISAC studies have been limited to operation within a single frequency band and have not been designed to adapt to diverse wireless propagation environments or user configurations. To address these limitations, this paper investigates a reconfigurable intelligent surface (RIS)-assisted ISAC system employing an adaptive bandwidth-splitting strategy under near-field (NF) and far-field (FF) coexistence. The system comprises a full-duplex access point (AP), an RIS and multiple users, where an ISAC user (IU) is both a sensing target and a communication user in the NF region, while communication-only users (CUs) rely on the RIS and experience either NF or FF propagation depending on their placement. The proposed system jointly exploits traditional sensing-only (SO) and ISAC bands and adopts uplink non-orthogonal multiple access (NOMA) for simultaneous transmission. We formulate a joint optimization problem for the receive beamforming vector, bandwidth-splitting ratio, and RIS phase shifts to minimize the Cramer-Rao bound (CRB) under rate and resource constraints. An efficient algorithm is developed based on an alternating optimization (AO) framework combined with semi-definite relaxation (SDR). Numerical results demonstrate that the proposed approach significantly outperforms conventional schemes that operate solely in either the ISAC or SO band, achieving superior performance across various RIS and user configurations under hybrid NF and FF coexistence scenarios.