基于低轨道卫星回程的5G及以上航空网络中的边缘智能

Babak Mafakheri, Chao Yan, Kiran Narayanaswamy, Isabelle Trang, Tobias Betz, Konrad Pientka, L. Goratti
{"title":"基于低轨道卫星回程的5G及以上航空网络中的边缘智能","authors":"Babak Mafakheri, Chao Yan, Kiran Narayanaswamy, Isabelle Trang, Tobias Betz, Konrad Pientka, L. Goratti","doi":"10.1109/EuCNC/6GSummit58263.2023.10188250","DOIUrl":null,"url":null,"abstract":"The vision of ubiquitous network connectivity to fuel uninterrupted services to any user has materialized with the Fifth-Generation (5G) of mobile technology and will probably find maturity on the way to developing 6G. To reach this goal, 5G technology and its evolution (B5G), as well as Multi-access Edge Computing (MEC), alongside Machine Learning (ML) will play pivotal roles. This work sheds light onto a test bed development and initial experimentation results obtained to enable airlines' passengers on-board an aircraft with broadband connectivity as an advancement toward ubiquitous access. We detail our research and experimentation activity as part of the H2020 AI@EDGE research project around a 5G network and an edge-cloud built on top of aviation-certified hardware and off-the-shelf servers. The edge-cloud is used to develop and test MEC applications that can be seen as the next generation of services offered to airlines and to airlines' passengers and that rely on machine learning. The 5G network is integrated into a larger test-bed and connected to a 5G core on the ground by means of a Low Earth Orbit (LEO) satellite backhaul such as Starlink.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"37 1","pages":"579-584"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Edge Intelligence in 5G and Beyond Aeronautical Network with LEO Satellite Backhaul\",\"authors\":\"Babak Mafakheri, Chao Yan, Kiran Narayanaswamy, Isabelle Trang, Tobias Betz, Konrad Pientka, L. Goratti\",\"doi\":\"10.1109/EuCNC/6GSummit58263.2023.10188250\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The vision of ubiquitous network connectivity to fuel uninterrupted services to any user has materialized with the Fifth-Generation (5G) of mobile technology and will probably find maturity on the way to developing 6G. To reach this goal, 5G technology and its evolution (B5G), as well as Multi-access Edge Computing (MEC), alongside Machine Learning (ML) will play pivotal roles. This work sheds light onto a test bed development and initial experimentation results obtained to enable airlines' passengers on-board an aircraft with broadband connectivity as an advancement toward ubiquitous access. We detail our research and experimentation activity as part of the H2020 AI@EDGE research project around a 5G network and an edge-cloud built on top of aviation-certified hardware and off-the-shelf servers. The edge-cloud is used to develop and test MEC applications that can be seen as the next generation of services offered to airlines and to airlines' passengers and that rely on machine learning. The 5G network is integrated into a larger test-bed and connected to a 5G core on the ground by means of a Low Earth Orbit (LEO) satellite backhaul such as Starlink.\",\"PeriodicalId\":65870,\"journal\":{\"name\":\"公共管理高层论坛\",\"volume\":\"37 1\",\"pages\":\"579-584\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"公共管理高层论坛\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188250\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"公共管理高层论坛","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

无处不在的网络连接为任何用户提供不间断服务的愿景已经随着第五代(5G)移动技术的实现而实现,并可能在发展6G的过程中走向成熟。为了实现这一目标,5G技术及其演进(B5G)、多接入边缘计算(MEC)以及机器学习(ML)将发挥关键作用。这项工作揭示了测试平台的开发和初步实验结果,使航空公司的乘客能够在飞机上使用宽带连接,这是向无处不在的接入迈进的一步。作为H2020 AI@EDGE研究项目的一部分,我们详细介绍了我们的研究和实验活动,该项目围绕5G网络和基于航空认证硬件和现成服务器构建的边缘云。边缘云用于开发和测试MEC应用程序,这些应用程序可以被视为提供给航空公司和航空公司乘客的下一代服务,并且依赖于机器学习。5G网络被集成到一个更大的试验台,并通过低地球轨道(LEO)卫星回程(如Starlink)与地面的5G核心相连。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Edge Intelligence in 5G and Beyond Aeronautical Network with LEO Satellite Backhaul
The vision of ubiquitous network connectivity to fuel uninterrupted services to any user has materialized with the Fifth-Generation (5G) of mobile technology and will probably find maturity on the way to developing 6G. To reach this goal, 5G technology and its evolution (B5G), as well as Multi-access Edge Computing (MEC), alongside Machine Learning (ML) will play pivotal roles. This work sheds light onto a test bed development and initial experimentation results obtained to enable airlines' passengers on-board an aircraft with broadband connectivity as an advancement toward ubiquitous access. We detail our research and experimentation activity as part of the H2020 AI@EDGE research project around a 5G network and an edge-cloud built on top of aviation-certified hardware and off-the-shelf servers. The edge-cloud is used to develop and test MEC applications that can be seen as the next generation of services offered to airlines and to airlines' passengers and that rely on machine learning. The 5G network is integrated into a larger test-bed and connected to a 5G core on the ground by means of a Low Earth Orbit (LEO) satellite backhaul such as Starlink.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
385
期刊最新文献
Undersampling and SNR Degradation in Practical Direct RF Sampling Systems Research Challenges in Trustworthy Artificial Intelligence and Computing for Health: The Case of the PRE-ACT project Inter-Satellite Link Prediction for Non-Terrestrial Networks Using Supervised Learning AI-Powered Edge Computing Evolution for Beyond 5G Communication Networks Phase Modulation-based Fronthaul Network for 5G mmWave FR-2 Signal Transmission over Hybrid Links
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1