This paper investigates an autonomous aerial vehicle (AAV)-enabled integrated sensing, communication, and computation system, with a particular focus on integrating movable antennas (MAs) into the system for enhancing overall system performance. Specifically, multiple MA-enabled AVVs perform sensing tasks and simultaneously transmit the generated computational tasks to the base station for processing. To minimize the maximum latency under the sensing and resource constraints, we formulate an optimization problem that jointly coordinates the position of the MAs, the computation resource allocation, and the transmit beamforming. Due to the non-convexity of the objective function and strong coupling among variables, we propose a two-layer iterative algorithm leveraging particle swarm optimization and convex optimization to address it. The simulation results demonstrate that the proposed scheme achieves significant latency improvements compared to the baseline schemes.

翻译：本文研究了一种基于自主飞行器（AAV）的集成感知、通信与计算系统，重点探讨将可移动天线（MAs）集成到系统中以提升整体性能。具体而言，多个配备可移动天线的AAV执行感知任务，并同时将生成的计算任务传输至基站进行处理。为了在感知与资源约束下最小化最大时延，我们构建了一个联合优化问题，协同优化可移动天线的位置、计算资源分配以及发射波束成形。由于目标函数的非凸性及变量间的强耦合性，我们提出了一种基于粒子群优化与凸优化的双层迭代算法进行求解。仿真结果表明，与基准方案相比，所提方案实现了显著的时延性能提升。