The Journal of China Universities of Posts and Telecommunications ›› 2022, Vol. 29 ›› Issue (1): 27-40.doi: 10.19682/j.cnki.1005-8885.2022.2004

• Special Topic: Intellicise Communication System • Previous Articles     Next Articles

Native intelligence for 6G mobile network: technical challenges, architecture and key features

Liu Guangyi, Deng Juan, Zheng Qingbi, Li Gang, Sun Xin, Huang Yuhong   

  1. Future Research Lab, China Mobile Research Institute, Beijing 100032, China
  • Received:2021-12-13 Revised:2022-01-19 Accepted:2022-01-25 Online:2022-02-26 Published:2022-02-28
  • Contact: Corresponding author: Zheng Qingbi
  • Supported by:
    This work was supported by the National Key R&D Program of China (2020YFB1806800).

Abstract: 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 ubiquitous intelligence 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.

Key words: the 5th generation mobile communication system, the 6th generation mobile communication system, artificial intelligence, native intelligence, network intelligence, network architecture, mobile communication

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