Full Text:   <27>

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On-line Access: 2025-03-07

Received: 2024-07-05

Revision Accepted: 2024-10-28

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Guangyi LIU

https://orcid.org/0000-0002-8656-1946

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Frontiers of Information Technology & Electronic Engineering  2025 Vol.26 No.2 P.161-213

http://doi.org/10.1631/FITEE.2400569


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


Author(s):  Guangyi LIU, Juan DENG, Yanhong ZHU, Na LI, Boxiao HAN, Shoufeng WANG, Hua RUI, Jingyu WANG, Jianhua ZHANG, Ying CUI, Yingping CUI, Yang YANG, Yan ZHANG, Jiangzhou WANG, Ye OUYANG, Xiaozhou YE, Tao CHEN, Rongpeng LI, Yongdong ZHU, Yuanyuan ZHANG, Li YANG, Sen BIAN, Wanfei SUN, Qingbi ZHENG, Zhou TONG, Huimin ZHANG, Zecai SHAO, Jiajun WU, Mancong KANG

Affiliation(s):  China Mobile Research Institute, Beijing 100053, China; more

Corresponding email(s):   liuguangyi@chinamobile.com

Key Words:  6G, Network autonomy, Native artificial intelligence, Network digital twin, Service-based radio access network


Guangyi LIU, Juan DENG, Yanhong ZHU, Na LI, Boxiao HAN, Shoufeng WANG, Hua RUI, Jingyu WANG, Jianhua ZHANG, Ying CUI, Yingping CUI, Yang YANG, Yan ZHANG, Jiangzhou WANG, Ye OUYANG, Xiaozhou YE, Tao CHEN, Rongpeng LI, Yongdong ZHU, Yuanyuan ZHANG, Li YANG, Sen BIAN, Wanfei SUN, Qingbi ZHENG, Zhou TONG, Huimin ZHANG, Zecai SHAO, Jiajun WU, Mancong KANG. 6G autonomous radio access network empowered by artificial intelligence and network digital twin[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(2): 161-213.

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author="Guangyi LIU, Juan DENG, Yanhong ZHU, Na LI, Boxiao HAN, Shoufeng WANG, Hua RUI, Jingyu WANG, Jianhua ZHANG, Ying CUI, Yingping CUI, Yang YANG, Yan ZHANG, Jiangzhou WANG, Ye OUYANG, Xiaozhou YE, Tao CHEN, Rongpeng LI, Yongdong ZHU, Yuanyuan ZHANG, Li YANG, Sen BIAN, Wanfei SUN, Qingbi ZHENG, Zhou TONG, Huimin ZHANG, Zecai SHAO, Jiajun WU, Mancong KANG",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="26",
number="2",
pages="161-213",
year="2025",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2400569"
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%A Na LI
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%A Hua RUI
%A Jingyu WANG
%A Jianhua ZHANG
%A Ying CUI
%A Yingping CUI
%A Yang YANG
%A Yan ZHANG
%A Jiangzhou WANG
%A Ye OUYANG
%A Xiaozhou YE
%A Tao CHEN
%A Rongpeng LI
%A Yongdong ZHU
%A Yuanyuan ZHANG
%A Li YANG
%A Sen BIAN
%A Wanfei SUN
%A Qingbi ZHENG
%A Zhou TONG
%A Huimin ZHANG
%A Zecai SHAO
%A Jiajun WU
%A Mancong KANG
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A1 - Yang YANG
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A1 - Yongdong ZHU
A1 - Yuanyuan ZHANG
A1 - Li YANG
A1 - Sen BIAN
A1 - Wanfei SUN
A1 - Qingbi ZHENG
A1 - Zhou TONG
A1 - Huimin ZHANG
A1 - Zecai SHAO
A1 - Jiajun WU
A1 - Mancong KANG
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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.

人工智能和数字孪生使能的6G自主无线接入网

刘光毅1,2,邓娟1,2,朱艳宏1,李娜1,2,韩伯骁2,王首峰3,芮华4,王敬宇5,张建华5,崔颖6,崔莹萍1,杨旸6,张彦7,王江舟8,欧阳晔3,叶晓舟3,陈滔9,李荣鹏10,朱永东11,张园园9,杨立4,边森3,孙万飞12,郑青碧1,佟舟1,张慧敏1,邵泽才1,吴佳骏1,康曼聪1
1中国移动研究院,中国北京市,100053
2中关村泛联移动通信技术创新应用研究院,中国北京市,100080
3亚信科技(中国)有限公司,中国北京市,100193
4中兴通讯股份有限公司,中国深圳市,518057
5北京邮电大学信息与通信工程学院,中国北京市,100876
6香港科技大学(广州)特斯联"数字世界"联合研究中心,中国广州市,511455
7奥斯陆大学信息工程学院,挪威奥斯陆市,0316
8肯特大学工程与数字艺术学院,英国坎特伯雷,CT2 7NZ
9联发科技(北京)有限公司,中国北京市,100015
10浙江大学信息与电子工程学院,中国杭州市,310058
11之江实验室,中国杭州市,311500
12中信科移动通信技术股份有限公司,中国北京市,100083
摘要:第六代(6G)移动网络将实现数字孪生与泛在智能的社会愿景。与仅专注于通信的第五代(5G)移动网络不同,6G移动网络需要内生支持诸如感知、计算、人工智能(Artificial Intelligence, AI)、大数据和安全等新功能,同时推动一切即服务(Everything as a Service, XaaS)的实现。尽管5G移动网络的部署已经证明网络自动化和智能化能够简化网络运维(Operation and Maintenance, O&M)的流程,但外部功能的增加却导致了服务效率低下和运维成本上升。因此,本研究提出一种6G自治无线接入网(Radio Access Network, RAN)的技术框架,旨在实现高水平的网络自治;该框架融合了云原生、内生AI和网络数字孪生(Network Digital Twin, NDT)的设计理念。首先,我们提出了服务化的架构,用于重新构建RAN的协议栈。这一架构能够按需灵活编排服务和功能,并将其定制为云原生服务。其次,我们构建了内生AI框架,通过编排AI用例所需的通信、AI模型、数据和计算能力,为网络运维的多样化用例提供AI支持。第三,我们引入了数字孪生网络,作为AI算法和神经网络的训练、预验证和调优的虚拟环境。这一环境能够避免AI应用可能给网络运维带来的风险。通过内生AI与NDT的结合,可以构建RAN的闭环管理和优化,进一步促进网络自治的实现。

关键词:6G;网络自治;内生人工智能;网络数字孪生;服务化无线接入网

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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