Movable Antenna-Aided Near-Field Integrated Sensing and Communication

2024-12-27

AI Summary

In near-field integrated sensing and communication (ISAC), conventional far-field channel assumptions break down, and large-scale spatial signal variations remain underexploited. Method: This work pioneers the integration of multiple movable antennas (MAs) at the base station in near-field ISAC systems, jointly optimizing beamforming, sensing covariance, uplink power allocation, and antenna positions. A two-layer Random Position (RP) algorithm is proposed to jointly maximize weighted sum-rate and sensing performance; a greedy Antenna Position Matching (APM) algorithm further minimizes total antenna displacement. Near-field channel modeling and full-duplex MIMO beamforming are incorporated. Contribution/Results: The proposed framework significantly enhances joint sensing-communication performance while reducing energy consumption and latency, thereby validating both the feasibility and superiority of the MA architecture for near-field ISAC.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Multiagent Systems: Agent Communication
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

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, while 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.

Problem

• Integrated Sensing and Communication (ISAC)
• Mobile Antenna (MA) Technology
• Near-field Environment

Innovation

• Mobile Antenna (MA) Technology
• Perception and Communication Efficiency Optimization
• Random Position (RP) Algorithm and Antenna Position Matching (APM) Algorithm