灾后无人机自组网高动态多信道TDMA调度算法
Highly dynamic multi-channel TDMA scheduling algorithm for the UAV ad hoc network in post-disaster
- 西安电子科技大学学报 2024年51卷第2期 页码：56-67
- 作者机构：
1. 中国矿业大学 信息与控制工程学院,江苏 徐州 221116
2. 中国矿业大学 物联网(感知矿山)研究中心,江苏 徐州 221008
- 作者简介：
[ "孙彦景(1977—),男,教授,E-mail:[email protected]; " ]
[ "李 林(1998—),男,中国矿业大学硕士研究生,E-mail:[email protected]; " ]
王博文(1994—),男,副教授,E-mail:[email protected]
[ "李 松(1985—),男,副教授,E-mail:[email protected]" ]
- 基金信息：国家自然科学基金(62101556);国家自然科学基金(62071472);江苏省自然科学基金(BK20210489);江苏省教育厅未来网络科研基金(FNSRFP-2021-YB-12);中国矿业大学“工业物联网与应急协同”创新团队资助计划(2020ZY002)
DOI：10.19665/j.issn1001-2400.20230414
中图分类号： TN929.5纸质出版日期：2024-4-20，
网络出版日期：2023-9-14，
收稿日期：2023-2-28，
扫 描 看 全 文
孙彦景, 李林, 王博文, 等. 灾后无人机自组网高动态多信道TDMA调度算法[J]. 西安电子科技大学学报, 2024,51(2):56-67.
Yanjing SUN, Lin LI, Bowen WANG, et al. Highly dynamic multi-channel TDMA scheduling algorithm for the UAV ad hoc network in post-disaster[J]. Journal of Xidian University, 2024,51(2):56-67.
孙彦景, 李林, 王博文, 等. 灾后无人机自组网高动态多信道TDMA调度算法[J]. 西安电子科技大学学报, 2024,51(2):56-67. DOI： 10.19665/j.issn1001-2400.20230414.
Yanjing SUN, Lin LI, Bowen WANG, et al. Highly dynamic multi-channel TDMA scheduling algorithm for the UAV ad hoc network in post-disaster[J]. Journal of Xidian University, 2024,51(2):56-67. DOI： 10.19665/j.issn1001-2400.20230414.
摘要
以自然灾害、事故灾难为主要类型的极端突发事件对应急通信网络快速重组与灾情信息实时回传提出了严峻挑战
亟需构建具备快速响应能力、按需动态调整的应急通信网络。为了在断电、断路、断网“三断”极端条件下实现灾情信息实时回传
可通过多无人机形成飞行自组网对受灾区域进行网络通信覆盖。针对灾后复杂环境受限条件下飞行自组织网络通信资源调度不合理引起的信道冲突问题
提出了基于
Q
-learning的自适应多信道时分多址调度算法。根据无人机间的链路干扰关系建立顶点干扰图
结合图着色理论
将高动态场景下多信道时分多址调度问题抽象为动态二重着色问题。考虑无人机的高速移动性
通过自适应调整
Q
-learning的学习因子
实现算法的收敛速度与最优解探索能力的权衡优化
以适应高动态的网络拓扑。通过仿真实验证明
所提算法可以实现网络通信冲突和收敛速度的权衡优化
能够解决灾后高动态场景下资源分配决策与快变拓扑适配问题。
Abstract
Extreme emergencies
mainly natural disasters and accidents
have posed serious challenges to the rapid reorganization of the emergency communication network and the real-time transmission of disaster information.It is urgent to build an emergency communication network with rapid response capabilities and dynamic adjustment on demand.In order to realize real-time transmission of disaster information under the extreme conditions of "three interruptions" of power failure
circuit interruption and network connection
the Flying Ad Hoc Network can be formed by many unmanned aerial vehicles to cover the network communication in the disaster-stricken area.Aiming at the channel collision problem caused by unreasonable scheduling of FANET communication resources under the limited conditions of complex environment after disasters
this paper proposes a multi-channel time devision multiple access(TDMA) scheduling algorithm based on adaptive
Q
-learning.According to the link interference relationship between UAVs
the vertex interference graph is established
and combined with the graph coloring theory
and the multi-channel TDMA scheduling problem is abstracted into a dynamic double coloring problem in highly dynamic scenarios.Considering the high-speed mobility of the UA
V
the learning factor of
Q
-learning is adaptively adjusted according to the change of network topology
and the trade-off optimization of the convergence speed of the algorithm and the exploration ability of the optimal solution is realized.Simulation experiments show that the proposed algorithm can realize the trade-off optimization of network communication conflict and convergence speed
and can solve the problem of resource allocation decision and fast-changing topology adaptation in post-disaster high-dynamic scenarios.
关键词
无人机多信道时分多址图论自适应Q-learning
Keywords
unmanned aerial vehiclesmulti-channel TDMAgraph theoryadaptive Q-learning
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