The Impact of Uniform Circular Array on Near-field ISAC

TL;DR

This paper introduces a novel UCA-based near-field ISAC framework that enhances joint positioning accuracy, derives bounds for different target locations, and proposes low-complexity algorithms outperforming traditional methods.

Contribution

The paper develops a new UCA-based near-field ISAC framework, derives analytical bounds for positioning, and proposes efficient algorithms for SPEB minimization in both coplanar and non-coplanar scenarios.

Findings

UCA improves positioning performance over planar arrays in coplanar cases.

The Fisher Information Matrix can be approximated as diagonal with minimal loss.

Proposed VQF algorithms outperform SDR in accuracy and complexity.

Abstract

A novel uniform circular array (UCA) based near-field (NF) integrated sensing and communication (ISAC) framework is proposed, where the Cylindrical coordinate is invoked to evaluate the joint positioning performance. The joint squared position error bound (SPEB) of the sensing target (ST) is derived for the coplanar and non-coplanar cases. For the coplanar case, where the ST is located in the coplanar region of the UCA, the approximate Cram{\'e}r-Rao bound (CRB) expressions for the separate angle and distance estimation are given by exploiting the uniform spherical wavefront model. A SPEB minimization problem is formulated with the constraints of communication requirement and power budget, where the closed-form solution to minimize the CRB of the angle is derived. Inspired by the close-form expression, a low complexity vector-based quadratic transformation (VQF) algorithm is proposed by invoking the Rayleigh quotient. For the non-coplanar case, where the ST is located beyond the coplanar region of the UCA, the separate CRBs over three-dimensional coordinates and the joint SPEB approximations are derived. To minimize the SPEB performance, the semi-definite relaxation (SDR) method and extended low-complexity VQF algorithm are proposed. Numerical results validated that i) the Fisher Information Matrix about angle and distance in NF propagation can be approximated as a diagonal matrix with the trinity loss; ii) Compared with the uniform planar array, the UCA achieve better positioning performance when ST located in the coplanar of the antenna array; and iii) the proposed VQF algorithms reach higher solution precision than conventional SDR algorithm with much less computation complexity.