%0 Journal Article
%A 邓娟
%A 黄宇红
%A 李刚
%A 刘光毅
%A 孙欣
%A 郑青碧
%T Native intelligence for 6G mobile network: technical challenges,
architecture and key features
%D 2022
%R 10.19682/j.cnki.1005-8885.2022.2004
%J 中国邮电高校学报（英文）
%P 27-40
%V 29
%N 1
%X The application of the artificial intelligence (AI) technology in the 5th generation mobile communication system
(5G) networks promotes the development of the mobile communication network and its application in vertical
industries, however, the application models of "patching" and "plug-in" have hindered the effect of AI
applications. Meanwhile, the application of AI in all walks of life puts forward requirements for new capabilities of
the future network, such as distributed training, real-time collaborative inference, local data processing, etc. ,
which require "native intelligence design” in future networks. This paper discusses the requirements of native
intelligence in the 6th generation mobile communication system (6G) networks from the perspectives of 5G
intelligent network challenges and the <span>“</span>ubiquitous intelligence<span>”</span> vision of 6G, and analyzes the technical challenges
of the AI workflows in its lifecycle and the AI as a service (AIaaS) in cloud network. The progress and deficiencies
of the current research on AI functional architecture in various industry organizations are summarized. The end-to-end functional architecture for native AI for 6G network and its three key technical characteristics are proposed:
quality of AI services (QoAIS) based AI service orchestration for its full lifecycle, deep integration of native AI
computing and communication, and integration of native AI and digital twin network. The directions of future
research are also prospected.
%U https://jcupt.bupt.edu.cn/CN/10.19682/j.cnki.1005-8885.2022.2004