6G autonomous radio access network empowered by artificial intelligence and network digital twin

Liu, Guangyi, Deng, Juan, Zhu, Yanhong, Li, Na, Han, Boxiao, Wang, Shoufeng, Rui, Hua, Wang, Jingyu, Zhang, Jianhua, Cui, Ying, and others. (2024) 6G autonomous radio access network empowered by artificial intelligence and network digital twin. Frontiers of Information Technology & Electronic Engineering, 26 (2). pp. 161-213. E-ISSN 2095-9230. (doi:10.1631/fitee.2400569) (KAR id:108953)

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Official URL: https://doi.org/10.1631/fitee.2400569

Abstract

The sixth-generation (6G) mobile network implements the social vision of digital twins and ubiquitous intelligence. Contrary to the fifth-generation (5G) mobile network that focuses only on communications, 6G mobile networks must natively support new capabilities such as sensing, computing, artificial intelligence (AI), big data, and security while facilitating Everything as a Service. Although 5G mobile network deployment has demonstrated that network automation and intelligence can simplify network operation and maintenance (O&M), the addition of external functionalities has resulted in low service efficiency and high operational costs. In this study, a technology framework for a 6G autonomous radio access network (RAN) is proposed to achieve a high-level network autonomy that embraces the design of native cloud, native AI, and network digital twin (NDT). First, a service-based architecture is proposed to re-architect the protocol stack of RAN, which flexibly orchestrates the services and functions on demand as well as customizes them into cloud-native services. Second, a native AI framework is structured to provide AI support for the diverse use cases of network O&M by orchestrating communications, AI models, data, and computing power demanded by AI use cases. Third, a digital twin network is developed as a virtual environment for the training, pre-validation, and tuning of AI algorithms and neural networks, avoiding possible unexpected losses of the network O&M caused by AI applications. The combination of native AI and NDT can facilitate network autonomy by building closed-loop management and optimization for RAN.

Item Type:	Article
DOI/Identification number:	10.1631/fitee.2400569
Uncontrolled keywords:	6G; network autonomy; native artificial intelligence; network digital twin; service-based radio access network
Subjects:	T Technology
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
SWORD Depositor:	JISC Publications Router
Depositing User:	JISC Publications Router
Date Deposited:	06 Mar 2025 11:27 UTC
Last Modified:	07 Mar 2025 09:46 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/108953 (The current URI for this page, for reference purposes)

University of Kent Author Information

Wang, Jiangzhou.

Creator's ORCID:	https://orcid.org/0000-0003-0881-3594
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