Optimal Beamforming Design for Multi-user MIMO Near-Field ISAC Systems with Movable Antennas

2025-12-27

AI Summary

This work addresses the joint optimization of movable antennas (MAs) in near-field integrated sensing and communication (ISAC) systems, aiming to maximize the weighted sum rate (WSR) of communication users under a minimum sensing signal-to-interference-plus-noise ratio (SINR) constraint. It is the first systematic study to incorporate antenna position optimization into a multi-user MIMO near-field ISAC framework, jointly designing communication precoders (linear and zero-forcing), sensing transmit/receive beams, and MA layouts at both base station and user sides. An efficient alternating optimization algorithm is proposed to synergistically enhance both communication and sensing performance. Compared with fixed-antenna configurations, the proposed method significantly improves WSR; linear precoding accommodates heterogeneous user weights, while zero-forcing precoding enhances rate fairness. Sensing performance exhibits high sensitivity to the SINR threshold, underscoring the necessity of joint optimization.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Applications
• Multiagent Systems: Agent Communication

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Novel mobile and WoT systems, and system-of-systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization

Abstract

Integrated sensing and communication (ISAC) has been recognized as one of the key technologies capable of simultaneously improving communication and sensing services in future wireless networks. Moreover, the introduction of recently developed movable antennas (MAs) has the potential to further increase the performance gains of ISAC systems. Although the gains of MA-enabled ISAC systems are relatively well studied in the far field, they remain almost unexplored in near-field scenarios. Motivated by this, in this paper we maximize the weighted sum rate (WSR) for communication users while maintaining a minimum sensing requirement in an MA-enabled near-field ISAC system. To achieve this goal, we propose algorithms that optimize the communication precoding matrices, the sensing transmit beamformer, the sensing receive combiner, the positions of the users' MAs and the positions of the base station (BS) transmit MAs in an alternating manner for the considered ISAC system, for the cases where linear procoding and zero-forcing (ZF) precoding are employed at the BS. Simulation results show that using MAs in near-field ISAC systems provides a substantial performance advantage compared to near-field ISAC systems equipped with fixed antennas only. We show that the scheme with linear precoding achieves larger WSR for unequal users' weight rates, while the scheme with ZF precoding maintains an approximately constant WSR for all users' weight rates. Additionally, we demonstrate that the WSRs of the proposed schemes are highly dependent on the inter-antenna interference between different user's MAs, and that the sensing performance is significantly more affected by the minimum sensing signal-to-interference-plus-noise ratio (SINR) threshold compared to the communication performance.

Problem

• Optimizes beamforming for multi-user MIMO near-field ISAC systems with movable antennas.
• Maximizes weighted sum rate for communication while ensuring minimum sensing requirements.
• Addresses performance gains of movable antennas in near-field scenarios, previously unexplored.

Innovation

• Optimizing movable antenna positions for near-field ISAC systems
• Alternating optimization of precoding, beamforming, and combiner
• Comparing linear and zero-forcing precoding performance trade-offs