Research on UAV network slicing resource management for low-altitude intelligent network

CHEN Hongjie; GUO Yufu; WU Fan; ZHANG Ke; XIONG Kai

doi:10.11959/j.issn.1000-0801.2025053

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Research on UAV network slicing resource management for low-altitude intelligent network

Topic：Low-Altitude Intelligent Network & Low-Altitude Security | 更新时间：2025-04-24

- Research on UAV network slicing resource management for low-altitude intelligent network
- Telecommunications Science Vol. 41, Issue 3, Pages: 38-51(2025)
- 作者机构：
  
  1.中国西南电子技术研究所，四川成都 610036
  2.电子科技大学信息与通信工程学院，四川成都 611731
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China Youth Project(62201122)
- DOI：10.11959/j.issn.1000-0801.2025053
  CLC： TN915.5
- Received：24 January 2025，
  
  Revised：2025-03-05，
  
  Published：20 March 2025
- 稿件说明：
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陈鸿杰,郭昱甫,吴凡等.面向低空智联网的无人机网络切片资源管理机制研究[J].电信科学,2025,41(03):38-51.

CHEN Hongjie,GUO Yufu,WU Fan,et al.Research on UAV network slicing resource management for low-altitude intelligent network[J].Telecommunications Science,2025,41(03):38-51.
陈鸿杰,郭昱甫,吴凡等.面向低空智联网的无人机网络切片资源管理机制研究[J].电信科学,2025,41(03):38-51. DOI： 10.11959/j.issn.1000-0801.2025053.

CHEN Hongjie,GUO Yufu,WU Fan,et al.Research on UAV network slicing resource management for low-altitude intelligent network[J].Telecommunications Science,2025,41(03):38-51. DOI： 10.11959/j.issn.1000-0801.2025053.

摘要

在低空智联网中，无人机作为空中通信基站、数据传输中继节点和移动网络终端的重要组成部分，凭借其卓越的机动性和适应性，广泛应用于扩展网络覆盖和支持多种业务服务。然而，由于低空智联网面临着网络拓扑动态变化、空域资源稀缺以及多样化业务需求等挑战，实现有限资源的高效编排和管理仍然是一项艰巨任务。为解决这一问题，通过对无人机网络进行端到端切片，构建满足特定需求的逻辑无人机网络架构。首先，设计了一种分群轨迹预测模型，用于确定分群接入节点的位置，为网络切片的资源预留与优化提供支持。基于此，提出了一种双时间尺度的资源管理框架：在大时间尺度上，采用非线性规划方法将切片重配置问题转化为约束优化问题，优化整体切片效益并合理预留资源；在小时间尺度上，通过针对切片内业务需求的资源调度策略，满足具体业务的传输服务质量（quality of service，QoS）需求。仿真结果表明，该方法增强了低空无人机智联网络在动态环境中的适应性与服务质量，为低空智联网复杂场景下的资源管理和业务保障提供了有效支持。

Abstract

In low-altitude intelligent networks

unmanned aerial vehicles (UAV) play a crucial role as aerial communication base stations

data relay nodes

and mobile network terminals. Leveraging their exceptional mobility and adaptability

UAV can extend network coverage and support a wide range of service applications. However

the challenges of dynamic network topology

constrained airspace resources

and diverse service demand pose significant difficulties in achieving efficient resource orchestration and management. To address these challenges

an end-to-end slicing approach for UAV network was introduced

enabling the construction of logical network architectures tailored to specific requirements. A cluster trajectory prediction model was developed to identify the positions of clustered access nodes

providing essential support for resource reservation and optimization in network slicing. Building on this

a dual time-scale resource management framework was proposed. At a larger time scale

the slice reconfiguration problem was transformed into a constrained optimization task by a nonlinear programming approach

maximizing overall slice efficiency and ensuring rational resource reservation. At a finer time scale

intra-slice resource scheduling strategies were implemented to meet the QoS requirements of specific services. Simulation results demonstrate that the proposed method significantly improves the communication performance of low-altitude dynamic intelligent networks. It enhances the adaptability and service quality of UAV network slicing in dynamic environments

offering effective support for resource management and service assurance in complex scenarios.

关键词

Keywords

references

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