ARTIFICIAL INTELLIGENCE-ASSISTED NETWORK SLICING Network Assurance and Service Provisioning in 6G

被引:28
|
作者
Wang, Jiadai [1 ]
Liu, Jiajia [1 ]
Li, Jingyi [2 ]
Kato, Nei [3 ]
机构
[1] Northwestern Polytech Univ, Sch Cybersecur, Xian 710072, Peoples R China
[2] Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China
[3] Tohoku Univ, Grad Sch Informat Sci, Sendai 9808579, Japan
来源
IEEE VEHICULAR TECHNOLOGY MAGAZINE | 2023年 / 18卷 / 01期
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
6G mobile communication; Network slicing; Quality of service; Data models; Predictive models; Vehicle dynamics; Bandwidth; 6G; RADIO;
D O I
10.1109/MVT.2022.3228399
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
6G networks are expected to provide instant global connectivity and enable the transition from "connected things " to "connected intelligence, " where promising network slicing can play an important role in network assurance and service provisioning for various demanding vertical application scenarios. On the basis of diversified massive data, artificial intelligence (AI)-assisted techniques are widely considered more suitable than traditional models and algorithms to deal with challenges faced by complex and dynamic slicing problems in 6G. In view of this, we provide a tutorial on AI-assisted 6G network slicing for network assurance and service provisioning, aiming to show the prospect of 6G slicing and the advantages of applying AI technology. Specifically, we propose six typical characteristics of 6G network slicing, analyze the feasibility of AI from different network domains and technical aspects, propose a case study on AI-assisted bandwidth scaling, and, finally, put forward the main challenges and open issues for its future development.
引用
收藏
页码:49 / 58
页数:10
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