Low-altitude wireless networks (LAWNs) are expected to consist of multi-tier, heterogeneous terrestrial and non-terrestrial devices, where effective coordination is essential to fully unlock the complementary capabilities of diverse systems from different vendors. To address this issue, we propose a novel multi-functional coordination framework that enables seamless cooperation within the LAWN while supporting efficient execution of diverse network functions. In the proposed architecture, each device or infrastructure element is assigned to a specific functional role, namely, edge mobile terminal (E-MT), distributed MT (D-MT), or computing center. E-MTs are equipped with lightweight, independent signal processing and computing capabilities, while D-MTs and the computing center handle regional and global coordination, respectively. To enhance the overall network efficiency, we model the LAWN as a sparse graph, where nodes represent network nodes and edges are defined according to a set of controllable connection rules. This topology-aware (TA) representation allows for efficiently solving various coordination tasks across the network. Numerical results show that the proposed TA coordination framework outperforms baseline approaches that lack topological insights, achieving higher efficiency in multi-task coordination. Finally, we discuss key technical challenges and outline potential solutions for future deployment.

翻译：低空无线网络预计将由多层异构的地面与非地面设备构成，其中有效的协同对于充分释放来自不同供应商的多样化系统的互补能力至关重要。为解决这一问题，本文提出了一种新颖的多功能协同框架，该框架能够在低空无线网络内实现无缝协作，同时支持多样化网络功能的高效执行。在所提出的架构中，每个设备或基础设施元素被分配一个特定的功能角色，即边缘移动终端、分布式移动终端或计算中心。边缘移动终端配备轻量级、独立的信号处理与计算能力，而分布式移动终端和计算中心则分别负责区域与全局协同。为提升整体网络效率，我们将低空无线网络建模为一个稀疏图，其中节点代表网络节点，边根据一组可控的连接规则定义。这种拓扑感知的表示方法能够高效解决网络中的各类协同任务。数值结果表明，所提出的拓扑感知协同框架优于缺乏拓扑洞察的基线方法，在多任务协同中实现了更高的效率。最后，我们讨论了关键技术挑战，并概述了未来部署的潜在解决方案。