CRLB Minimization for ISAC Systems with Segmented Waveguide-Enabled Pinching Antenna

TL;DR

This paper proposes a SWAN-assisted ISAC system that minimizes CRLB for target localization by jointly optimizing beamforming and antenna positioning using Riemannian manifold optimization.

Contribution

It introduces a novel RMO-based method for joint beamforming and antenna placement optimization in SWAN-assisted ISAC systems, improving localization accuracy.

Findings

SWAN-assisted ISAC outperforms existing schemes in CRLB for target localization.

The RMO method effectively optimizes beamforming and PA positions under constraints.

Simulation results confirm the superior localization performance of the proposed system.

Abstract

Pinching-antenna (PA) has recently attracted considerable research attention in wireless systems, realized by attaching small dielectric particles along a waveguide. Building upon which, the segmented waveguide-enabled pinching-antenna system (SWAN) has been proposed to mitigate the inter-antenna radiation problem in uplink transmissions of conventional PA systems. In this work, SWAN-assisted integrated sensing and communication (ISAC) is investigated, where a base station (BS) equipped with SWAN provides downlink communications for multiple communication users (CUs) and performs sensing for multiple targets. The dual-functional signals transmitted by the BS are radiated by the SWAN, and the echo signals reflected by the targets are captured by the SWAN and relayed to the BS for estimating the locations of the targets. We formulate a Cram\'er-Rao lower bound (CRLB) minimization problem to evaluate the performance of the ISAC system, where the CRLB of the location estimation is minimized under communication rate constraints. To jointly optimize the beamforming and the PA positions of the SWAN, we develop a Riemannian manifold optimization (RMO) method, where each variable is constrained on its corresponding Riemannian manifold, and a Riemannian product manifold (RPM) is constructed as the solution space. A penalty method combined with Riemannian Broyden-Fletcher-Goldfarb-Shanno (RBFGS) algorithm is applied to obtain a feasible solution. Simulation results show that the proposed SWAN-assisted ISAC system yields superior CRLB performance for target localization compared with existing schemes including the multi-waveguide-enabled pinching-antenna-assisted ISAC systems.