Movable Antenna-Aided Near-Field Integrated Sensing and Communication

TL;DR

This paper explores the use of movable antennas in near-field integrated sensing and communication systems to enhance performance, optimize antenna positioning, and reduce movement costs, addressing limitations of fixed-position antennas.

Contribution

It introduces a novel near-field ISAC system with movable antennas, proposing algorithms for joint optimization of beamforming, antenna positions, and power allocation.

Findings

Significant performance improvements with movable antennas.

Effective algorithms for antenna position optimization.

Reduced antenna movement distance and energy consumption.

Abstract

Integrated sensing and communication (ISAC) is emerging as a pivotal technology for next-generation wireless networks. However, existing ISAC systems are based on fixed-position antennas (FPAs), which inevitably incur a loss in performance when balancing the trade-off between sensing and communication. Movable antenna (MA) technology offers promising potential to enhance ISAC performance by enabling flexible antenna movement. Nevertheless, exploiting more spatial channel variations requires larger antenna moving regions, which may invalidate the conventional far-field assumption for channels between transceivers. Therefore, this paper utilizes the MA to enhance sensing and communication capabilities in near-field ISAC systems, where a full-duplex base station (BS) is equipped with multiple transmit and receive MAs movable in large-size regions to simultaneously sense multiple targets and serve multiple uplink (UL) and downlink (DL) users for communication. We aim to maximize the weighted sum of sensing and communication rates (WSR) by jointly designing the transmit beamformers, sensing signal covariance matrices, receive beamformers, and MA positions at the BS, as well as the UL power allocation. The resulting optimization problem is challenging to solve. Thus, we propose an efficient two-layer random position (RP) algorithm to tackle it. In addition, to reduce movement delay and cost, we design an antenna position matching (APM) algorithm based on the greedy strategy to minimize the total MA movement distance. Extensive simulation results demonstrate the substantial performance improvement achieved by deploying MAs in near-field ISAC systems. Moreover, the results show the effectiveness of the proposed APM algorithm in reducing the antenna movement distance, which is helpful for energy saving and time overhead reduction for MA-aided near-field ISAC systems with large moving regions.