基于联盟的6G无人机通信网络优化概述

陈润丰; 陈瑾; 李虹; 初晓婧; 刘典雄; 张玉立; 徐煜华

doi:10.11999/JEIT220383

基于联盟的6G无人机通信网络优化概述

doi: 10.11999/JEIT220383

1.
陆军工程大学通信工程学院南京 210014
2.
中国人民解放军96963部队南京 210000
3.
军事科学院系统工程研究院北京 100141
4.
军事科学院国防科技创新研究院北京 100071

基金项目: 国家自然科学基金(61771488, 61901506, 62101584)

详细信息

作者简介:
陈润丰：男，博士生，研究方向为无人系统用频和大规模网络资源优化

陈瑾：女，教授，研究方向为短波通信

李虹：女，高级工程师，研究方向为无线通信

初晓婧：女，讲师，研究方向为无线通信

刘典雄：男，工程师，研究方向为集群通信

张玉立：男，助理研究员，研究方向为博弈论和频谱资源管理

徐煜华：男，教授，研究方向为无人集群通信和智能频谱对抗

通讯作者:
陈瑾　chenjin99@263.net

中图分类号: TN929.52; V279
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- 被引次数: 0
出版历程
- 收稿日期: 2022-04-01
- 修回日期: 2022-06-29
- 网络出版日期: 2022-07-04
- 刊出日期: 2022-09-19

Survey on Optimizations in Coalitions-based Unmanned Aerial Vehicle Communication Networks for 6G Networks

1.
Institute of Communication Engineering, Army Engineering University, Nanjing 210014, China
2.
PLA 96963 Troops, Nanjing 210000, China
3.
Institute of Systems Engineering, Academy of Military Sciences, Beijing 100141, China
4.
National Innovation Institute of Defense Technology, Academy of Military Sciences, Beijing 100071, China

Funds: The National Natural Science Foundation of China (61771488, 61901506, 62101584)

摘要

摘要: 随着6G网络和无人机(UAV)技术的迅猛发展，无人机通信网络将成为6G空天地一体化网络融合的关键组成部分，在战场侦查、野外救援和物联网信息传输等民用和军用领域发挥重要作用。针对无人机群大规模、高动态和自组织等特性，以6G网络任务驱动为出发点，该文提出基于联盟的6G无人机通信网络优化框架。围绕联盟形成、联盟任务实施和联盟资源管理对无人机联盟工作原理展开论述。结合博弈论、机器学习和在线决策，给出了无人机通信网络资源优化方法和仿真示例。最后，对6G无人机通信网络的应用前景和亟需解决的问题进行了开放性讨论。
- 6G /
- 无人机通信网络 /
- 联盟 /
- 任务驱动 /
- 博弈论
Abstract: With the rapid development of the Sixth Generation (6G) mobile communications and Unmanned Aerial Vehicle (UAV) technology, UAV communication networks become the key part of intelligent space-air-ground integration networks in 6G, which play an important role in battlefield reconnaissance, field rescue, information transmission of Internet of things and other military and civilian fields. Considering the characteristics of UAV networks such as large-scale, high-dynamic and self-organization, mission-driven UAV networks model based on coalitions for 6G is proposed. The model is discussed in three aspects: coalition formations, mission executions, and resource management. Combined with game theory, machine learning and online decisions, the optimization methods and simulation examples of UAV coalition networks are given. Finally, the application prospect of 6G UAV communication networks and the problems to be solved are discussed.
- 6G /
- Unmanned Aerial Vehicle (UAV) communication networks /
- Coalitions /
- Mission-driven /
- Game theory

HTML全文

图 1 无人机联盟通信网络示意图

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图 2 无人机联盟通信网络模型框架图

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图 3 无人机联盟网络调整示意图

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图 4 无人机联盟通信网络频谱资源管理

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图 5 基于博弈学习的人工智能优化框架

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图 6 无人机联盟通信组网仿真示意图

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图 7 博弈学习算法仿真示意图

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