发表机构
Tsinghua University; Nanjing University of Aeronautics and Astronautics（清华大学; 南京航空航天大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对低空经济中异构飞行器群的任务效率优化，提出基于运行能力熵的适应性功率分配方法，通过分解凸子问题求解，显著提升任务效率。
AI 中文摘要
随着低空经济的快速发展，低空作业蓬勃发展，其中复杂任务需要多种异构低空飞行器（LAAs）之间的协同努力。具体而言，不同的LAA承担不同的角色：一些用于感知，一些用于通信，一些用于计算，还有一些用于任务执行，共同形成一个类似反射弧的感知-通信-计算-控制（SC3）闭环。为了在这种多LAA群中实现高效协调，我们引入了运行能力熵（OCE）的概念，以量化运行中LAA的有效工作能力。据此，通过联合考虑异构OCE和LAA之间的信道条件，我们制定了功率分配问题，目标是最小化线性二次调节器（LQR）成本，该成本作为任务效率的度量。由此产生的复杂优化问题被分解为两个凸子问题，并迭代求解，每个子问题都得到了闭式解。仿真结果表明，所提出的面向任务的适应性功率分配方案显著优于传统方案。
英文摘要
With the rapid development of the low-altitude economy, low-altitude operations are booming, where complex missions require collaborative efforts among multiple heterogeneous low-altitude aircrafts (LAAs). Specifically, different LAAs assume distinct roles: some for sensing, some for communication, some for computing, and others for mission execution, together forming a sensing-communication-computing-control (SC3) closed loop, akin to a reflex arc. To enable efficient coordination in such multi-LAA swarms, we introduce the concept of operational-capability entropy (OCE) to quantify the effective work capability of operational LAAs. Accordingly, by jointly considering heterogeneous OCE and channel conditions among LAAs, we formulate the power allocation problem with the goal of minimizing the linear quadratic regulator (LQR) cost, which serves as a metric for mission efficiency. The resulting complex optimization problem is decomposed into two convex subproblems that are solved iteratively, with closed-form solutions derived for each. Simulation results demonstrate that the proposed mission-oriented adaptive power allocation scheme significantly outperforms traditional ones.
