Trajectory-Driven Beamforming Optimization: A Unified Framework for Mobile ISAC Agents

作者：Wenjun Hou, Xu Zhu, Zhongxiang Wei, Zhihao Dong, Jie Cao, Yufei Jiang, Vincent K. N. Lau · 发表于：IEEE Transactions on Network Science and Engineering · 年份：2025 · DOI：10.1109/tnse.2025.3622726 · 被引用次数：2 · 研究领域：Mobile Agent-Based Network Management、Mobile Ad Hoc Networks、Modular Robots and Swarm Intelligence

This paper investigates a practical dynamic scenario in an integrated sensing and communication (ISAC) system, where a mobile agent concurrently communicates with multiple users while sensing a mobile target. The simultaneous mobility of both the agent and the target introduces considerable complexity into the design of beamforming and trajectory optimization, rendering algorithms designed for static ISAC systems inadequate. To address this challenge, we propose a novel framework that integrates real-time prediction and tracking of the target state, beamforming, and agent trajectory design. Specifically, we develop a new algorithm that leverages the optimized trajectory of the mobile agent to predict and track the real-time states of the mobile target. Subsequently, the Cramér-Rao Bound (CRB) expressions for angle and distance estimation are derived, offering theoretical guidance for subsequent optimization and design. A joint CRB minimization problem is formulated to simultaneously optimize beamforming and the mobile agent's trajectory. Constraints on the agent's maximum speed and transmit power, as well as the communication quality-of-service (QoS) requirements of the users, are strictly enforced. This optimization problem poses significant challenges due to the dynamic coupling between the trajectory and beamforming variables, leading to a multi-dimensional and highly non-convex formulation. Moreover, the trajectory variable is embedded within a complex composite function....