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面向拓扑的多功能低空无线网络协调

Topology-Aware Coordination for Multi-Functional Low-Altitude Wireless Networks

Queen’s University Belfast(贝尔法斯特女王大学);Technical University of Berlin(柏林工业大学);Beijing Jiaotong University(北京交通大学);Southeast University(东南大学);City University of Hong Kong(香港城市大学)

Jiajun He, Han Yu, Yiran Guo, Xinping Yi, Fan Liu, Hing Cheung So, Hien Quoc Ngo, Michail Matthaiou, Giuseppe Caire

AI总结:

本文提出了一种面向拓扑的多功能低空无线网络协调框架,通过合理分配设备功能角色提升网络效率和多任务协调能力。

摘要:

低空无线网络(LAWNs)预计由多层、异构的地面和非地面设备组成,其中有效的协调对于充分释放不同供应商系统的互补能力至关重要。为了解决这一问题,我们提出了一种新的多功能协调框架,该框架能够在LAWN内实现无缝合作,同时支持高效的多样化网络功能执行。在所提出的架构中,每个设备或基础设施元素被分配到特定的功能角色,即边缘移动终端(E-MT)、分布式MT(D-MT)或计算中心。E-MTs配备了轻量级、独立的信号处理和计算能力,而D-MTs和计算中心分别负责区域和全球协调。为了提高整体网络效率,我们将LAWN建模为稀疏图,其中节点代表网络节点,边由一组可控的连接规则定义。这种面向拓扑(TA)的表示方法允许高效地解决网络中的各种协调任务。数值结果表明,所提出的TA协调框架优于缺乏拓扑洞察的基线方法,在多任务协调中实现更高的效率。最后,我们讨论了关键的技术挑战,并概述了未来部署的潜在解决方案。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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