斗兽场:开放式 RAN 数字双胞胎

IF 6.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Open Journal of the Communications Society Pub Date : 2024-08-22 DOI:10.1109/OJCOMS.2024.3447472
Michele Polese;Leonardo Bonati;Salvatore D'Oro;Pedram Johari;Davide Villa;Sakthivel Velumani;Rajeev Gangula;Maria Tsampazi;Clifton Paul Robinson;Gabriele Gemmi;Andrea Lacava;Stefano Maxenti;Hai Cheng;Tommaso Melodia
{"title":"斗兽场:开放式 RAN 数字双胞胎","authors":"Michele Polese;Leonardo Bonati;Salvatore D'Oro;Pedram Johari;Davide Villa;Sakthivel Velumani;Rajeev Gangula;Maria Tsampazi;Clifton Paul Robinson;Gabriele Gemmi;Andrea Lacava;Stefano Maxenti;Hai Cheng;Tommaso Melodia","doi":"10.1109/OJCOMS.2024.3447472","DOIUrl":null,"url":null,"abstract":"Recent years have witnessed the Open Radio Access Network (RAN) paradigm transforming the fundamental ways cellular systems are deployed, managed, and optimized. This shift is led by concepts such as openness, softwarization, programmability, interoperability, and intelligence of the network, which have emerged in wired networks through Software-defined Networking (SDN) but lag behind in cellular systems. The realization of the Open RAN vision into practical architectures, intelligent data-driven control loops, and efficient software implementations, however, is a multifaceted challenge, which requires (i) datasets to train Artificial Intelligence (AI) and Machine Learning (ML) models; (ii) facilities to test models without disrupting production networks; (iii) continuous and automated validation of the RAN software; and (iv) significant testing and integration efforts. This paper is a tutorial on how Colosseum—the world’s largest wireless network emulator with hardware in the loop—can provide the research infrastructure and tools to fill the gap between the Open RAN vision, and the deployment and commercialization of open and programmable networks. We describe how Colosseum implements an Open RAN digital twin through a high-fidelity Radio Frequency (RF) channel emulator and endto- end softwarized O-RAN and 5G-compliant protocol stacks, thus allowing users to reproduce and experiment upon topologies representative of real-world cellular deployments. Then, we detail the twinning infrastructure of Colosseum, as well as the automation pipelines for RF and protocol stack twinning. Finally, we showcase a broad range of Open RAN use cases implemented on Colosseum, including the real-time connection between the digital twin and real-world networks, and the development, prototyping, and testing of AI/ML solutions for Open RAN.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643670","citationCount":"0","resultStr":"{\"title\":\"Colosseum: The Open RAN Digital Twin\",\"authors\":\"Michele Polese;Leonardo Bonati;Salvatore D'Oro;Pedram Johari;Davide Villa;Sakthivel Velumani;Rajeev Gangula;Maria Tsampazi;Clifton Paul Robinson;Gabriele Gemmi;Andrea Lacava;Stefano Maxenti;Hai Cheng;Tommaso Melodia\",\"doi\":\"10.1109/OJCOMS.2024.3447472\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent years have witnessed the Open Radio Access Network (RAN) paradigm transforming the fundamental ways cellular systems are deployed, managed, and optimized. This shift is led by concepts such as openness, softwarization, programmability, interoperability, and intelligence of the network, which have emerged in wired networks through Software-defined Networking (SDN) but lag behind in cellular systems. The realization of the Open RAN vision into practical architectures, intelligent data-driven control loops, and efficient software implementations, however, is a multifaceted challenge, which requires (i) datasets to train Artificial Intelligence (AI) and Machine Learning (ML) models; (ii) facilities to test models without disrupting production networks; (iii) continuous and automated validation of the RAN software; and (iv) significant testing and integration efforts. This paper is a tutorial on how Colosseum—the world’s largest wireless network emulator with hardware in the loop—can provide the research infrastructure and tools to fill the gap between the Open RAN vision, and the deployment and commercialization of open and programmable networks. We describe how Colosseum implements an Open RAN digital twin through a high-fidelity Radio Frequency (RF) channel emulator and endto- end softwarized O-RAN and 5G-compliant protocol stacks, thus allowing users to reproduce and experiment upon topologies representative of real-world cellular deployments. Then, we detail the twinning infrastructure of Colosseum, as well as the automation pipelines for RF and protocol stack twinning. Finally, we showcase a broad range of Open RAN use cases implemented on Colosseum, including the real-time connection between the digital twin and real-world networks, and the development, prototyping, and testing of AI/ML solutions for Open RAN.\",\"PeriodicalId\":33803,\"journal\":{\"name\":\"IEEE Open Journal of the Communications Society\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2024-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643670\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Open Journal of the Communications Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10643670/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of the Communications Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10643670/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

近年来,开放式无线接入网(RAN)范例改变了蜂窝系统部署、管理和优化的基本方式。这一转变由开放性、软化、可编程性、互操作性和网络智能化等概念引领,这些概念已通过软件定义网络(SDN)在有线网络中出现,但在蜂窝系统中却相对滞后。然而,要将开放式 RAN 的愿景转化为实用的架构、智能数据驱动的控制回路和高效的软件实施,却是一项多方面的挑战,这需要:(i) 用于训练人工智能 (AI) 和机器学习 (ML) 模型的数据集;(ii) 在不中断生产网络的情况下测试模型的设施;(iii) RAN 软件的持续和自动验证;以及 (iv) 大量的测试和集成工作。本文将介绍 Colosseum(世界上最大的无线网络仿真器)如何提供研究基础设施和工具,以填补开放式 RAN 愿景与开放式可编程网络的部署和商业化之间的空白。我们将介绍 Colosseum 如何通过高保真射频(RF)信道仿真器和端到端软化 O-RAN 和 5G 兼容协议栈实现开放 RAN 数字孪生,从而让用户能够重现和实验代表真实世界蜂窝部署的拓扑结构。然后,我们将详细介绍 Colosseum 的孪生基础设施,以及射频和协议栈孪生的自动化管道。最后,我们将展示在 Colosseum 上实现的各种开放式 RAN 用例,包括数字孪生和真实世界网络之间的实时连接,以及开放式 RAN 的 AI/ML 解决方案的开发、原型设计和测试。
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
Colosseum: The Open RAN Digital Twin
Recent years have witnessed the Open Radio Access Network (RAN) paradigm transforming the fundamental ways cellular systems are deployed, managed, and optimized. This shift is led by concepts such as openness, softwarization, programmability, interoperability, and intelligence of the network, which have emerged in wired networks through Software-defined Networking (SDN) but lag behind in cellular systems. The realization of the Open RAN vision into practical architectures, intelligent data-driven control loops, and efficient software implementations, however, is a multifaceted challenge, which requires (i) datasets to train Artificial Intelligence (AI) and Machine Learning (ML) models; (ii) facilities to test models without disrupting production networks; (iii) continuous and automated validation of the RAN software; and (iv) significant testing and integration efforts. This paper is a tutorial on how Colosseum—the world’s largest wireless network emulator with hardware in the loop—can provide the research infrastructure and tools to fill the gap between the Open RAN vision, and the deployment and commercialization of open and programmable networks. We describe how Colosseum implements an Open RAN digital twin through a high-fidelity Radio Frequency (RF) channel emulator and endto- end softwarized O-RAN and 5G-compliant protocol stacks, thus allowing users to reproduce and experiment upon topologies representative of real-world cellular deployments. Then, we detail the twinning infrastructure of Colosseum, as well as the automation pipelines for RF and protocol stack twinning. Finally, we showcase a broad range of Open RAN use cases implemented on Colosseum, including the real-time connection between the digital twin and real-world networks, and the development, prototyping, and testing of AI/ML solutions for Open RAN.
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
CiteScore
13.70
自引率
3.80%
发文量
94
审稿时长
10 weeks
期刊介绍: The IEEE Open Journal of the Communications Society (OJ-COMS) is an open access, all-electronic journal that publishes original high-quality manuscripts on advances in the state of the art of telecommunications systems and networks. The papers in IEEE OJ-COMS are included in Scopus. Submissions reporting new theoretical findings (including novel methods, concepts, and studies) and practical contributions (including experiments and development of prototypes) are welcome. Additionally, survey and tutorial articles are considered. The IEEE OJCOMS received its debut impact factor of 7.9 according to the Journal Citation Reports (JCR) 2023. The IEEE Open Journal of the Communications Society covers science, technology, applications and standards for information organization, collection and transfer using electronic, optical and wireless channels and networks. Some specific areas covered include: Systems and network architecture, control and management Protocols, software, and middleware Quality of service, reliability, and security Modulation, detection, coding, and signaling Switching and routing Mobile and portable communications Terminals and other end-user devices Networks for content distribution and distributed computing Communications-based distributed resources control.
期刊最新文献
Applied Federated Model Personalization in the Industrial Domain: A Comparative Study Federated Learning: Challenges, SoTA, Performance Improvements and Application Domains A Worst-Case Latency and Age Analysis of Coded Distributed Computing With Unreliable Workers and Periodic Tasks Sparse Bayesian Learning Using Complex t-Prior for Beam-Domain Massive MIMO Channel Estimation Privacy-Preserving Hierarchical Reinforcement Learning Framework for Task Offloading in Low-Altitude Vehicular Fog Computing
×
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