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| An intelligent self-sustained RAN slicing framework for diverse service provisioning in 5G-beyond and 6G networks |
Jie Mei( ),Xianbin Wang*(),Kan Zheng() |
Electrical and Computer Engineering, Western University, London, ON N6A 5B9, Canada
Intelligent Computing and Communication (IC2) Lab, Wireless Signal Processing and Network (WSPN) Lab, Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts and Telecommunications (BUPT), Beijing 100876, China |
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Abstract Network slicing is a key technology to support the concurrent provisioning of heterogeneous Quality of Service (QoS) in the 5th Generation (5G)-beyond and the 6th Generation (6G) networks. However, effective slicing of Radio Access Network (RAN) is very challenging due to the diverse QoS requirements and dynamic conditions in the 6G networks. In this paper, we propose a self-sustained RAN slicing framework, which integrates the self-management of network resources with multiple granularities, the self-optimization of slicing control performance, and self-learning together to achieve an adaptive control strategy under unforeseen network conditions. The proposed RAN slicing framework is hierarchically structured, which decomposes the RAN slicing control into three levels, i.e., network-level slicing, next generation NodeB (gNodeB)-level slicing, and packet scheduling level slicing. At the network level, network resources are assigned to each gNodeB at a large timescale with coarse resource granularity. At the gNodeB-level, each gNodeB adjusts the configuration of each slice in the cell at the large timescale. At the packet scheduling level, each gNodeB allocates radio resource allocation among users in each network slice at a small timescale. Furthermore, we utilize the transfer learning approach to enable the transition from a model-based control to an autonomic and self-learning RAN slicing control. With the proposed RAN slicing framework, the QoS performance of emerging services is expected to be dramatically enhanced.
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Received: 30 July 2020
Online: 19 August 2021
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Corresponding Authors:
Xianbin Wang
E-mail: jmei28@uwo.ca;xianbin.wang@uwo.ca;zkan@bupt.edu.cn
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| About author: Jie Mei received the BS degree from Nanjing University of Posts and Telecommunications (NJUPT), China in 2013. He received the PhD degree from Beijing University of Posts and Telecommunications (BUPT) in 2019. Since August 2019, he has been a postdoctoral associate at Electrical and Computer Engineering, Western University, Canada. His research interests include intelligent communications and V2X communication.|Xianbin Wang received the PhD degree in electrical and computer engineering from National University of Singapore in 2001. He is a professor and Tier 1 Canada Research Chair at Western University, Canada. Prior to joining Western University, he was a research scientist/senior research scientist at Communications Research Centre Canada (CRC) between July 2002 and December 2007. From January 2001 to July 2002, he was a system designer at STMicroelectronics. His current research interests include 5G and beyond, Internet-of-Things, communications security, machine learning, and intelligent communications. He has over 400 peer-reviewed journal and conference papers, in addition to 30 granted and pending patents and several standard contributions. He is a fellow of Canadian Academy of Engineering, a fellow of Engineering Institute of Canada, a fellow of IEEE, and an IEEE distinguished lecturer. He has received many awards and recognitions, including Canada Research Chair, CRC President’s Excellence Award, Canadian Federal Government Public Service Award, Ontario Early Researcher Award, and six IEEE Best Paper Awards. He currently serves as an editor/associate editor for IEEE Transactions on Communications, IEEE Transactions on Broadcasting, and IEEE Transactions on Vehicular Technology. He was also an associate editor for IEEE Transactions on Wireless Communications between 2007 and 2011 and IEEE Wireless Communications Letters between 2011 and 2016. He was involved in many IEEE conferences including GLOBECOM, ICC, VTC, PIMRC, WCNC, and CWIT, in different roles such as symposium chair, tutorial instructor, track chair, session chair, and TPC co-chair. He is currently serving as the vice chair of IEEE London Section and the chair of ComSoc Signal Processing and Computing for Communications Technical Committee.|Kan Zheng received the BS, MS, and PhD degrees from Beijing University of Posts and Telecommunications, China in 1996, 2000, and 2005, respectively. He is currently a full professor at Beijing University of Posts and Telecommunications, China. He has rich experiences on the research and standardization of new emerging technologies. He is the author of more than 200 journal articles and conference papers in the field of vehicular networks, Internet-of-Things, machine learning, and so on. He holds editorial board positions for several journals and has organized several special issues. He has also served in the Organizing/TPC Committees for more than ten conferences, such as IEEE PIMRC, IEEE SmartGrid, and so on. |
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