地下空间应急场景无人机信道选择实验设计  

Experimental design of unmanned aerial vehicle channel selection for emergency scenarios in underground spaces

作　　者：王博文 聂同[1] 和孜轩 胡文信 WANG Bowen;NIE Tong;HE Zixuan;HU Wenxin(School of Information and Control Engineering,China University of Mining and Technology,Xuzhou 221116,China;Internet of Things Research Center,China University of Mining and Technology,Xuzhou 221116,China)

机构地区：[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研究中心,江苏徐州221116

出　　处：《实验技术与管理》2024年第10期109-115,共7页Experimental Technology and Management

基　　金：中国矿业大学教学学术研究项目(2022ZDKT03-203);国家自然科学基金项目(62101556);江苏省青年基金项目(BK20210489)。

摘　　要：近年来,地下空间灾害事故多发频发,利用全地形可灵活部署的无人机快速回传灾情数据是现代化应急管理体系建设的关键任务,电子信息等相关专业教学亟须进行面向地下空间的无人机应急通信网络实验和仿真。该文结合超图理论提出基于Q-learning的自适应动态信道选择算法,并利用ns-3网络仿真平台对网络环境模拟和网络性能测试进行了仿真实验设计,验证了该算法具有在高动态场景下有效提升网络平均吞吐量的能力,可为无人机应急通信网络场景化教学实践平台的建设打下坚实基础。[Objective]Recently,underground space disasters have occurred with increasing frequency,highlighting the urgent need for a comprehensive,multidimensional support system for emergency communication.A key task in emergency communication for underground spaces is the rapid reorganization of communication networks to relay disaster information in real time.Unmanned aerial vehicles(UAVs),with their flexible deployment,unmanned operation,and all-terrain mobility,can play a vital role in emergency rescue efforts.In the event of disasters such as fires,collapses,or floods,UAVs can quickly access affected areas and establish stable ad-hoc networks using their onboard communication devices.UAVs can promptly transmit the collected disaster information back to the rescue center,thereby enhancing the efficiency of rescue operations.However,while extensive research has been conducted on UAV applications in low-altitude areas,further development is necessary for their use in underground spaces.Particularly,there is a lack of research on experimental platforms that integrate scientific research and teaching.This gap has resulted in a disconnect between the educational content and real-world scenarios.Therefore,establishing a scenario-based teaching and practice platform for emergency communication networks in underground spaces is essential.By enhancing practical teaching content,we can effectively guide students in learning modern emergency communication network technologies,ensuring a strong connection between theoretical instruction and real-world applications.[Methods]In this paper,we employ hypergraph theory to abstract the rapidly changing network topology into a dynamically evolving hypergraph,modeling the evolution of interference relations through the insertion and deletion of superedges.Specifically,we reformulate the dynamic channel selection problem in UAV communication networks as a hypergraph coloring problem.To adapt to the dynamic network topology,we leverage reinforcement learning theory to enhance the tradition

关 键 词：地下空间应急通信 无人机通信 ns-3仿真 资源分配 Q-LEARNING 

分 类 号：TP929.4[自动化与计算机技术]