Overview of AI and communication for 6G network: fundamentals, challenges, and future research opportunities

Qimei Cui, Xiaohu You*, Ni Wei, Guoshun Nan*, Xuefei Zhang, Jianhua Zhang, Xinchen Lyu, Ming Ai, Xiaofeng Tao, Zhiyong Feng, Ping Zhang, Qingqing Wu, Meixia Tao, Yongming Huang, Chongwen Huang, Guangyi Liu, Chenghui Peng, Zhiwen Pan, Tao Sun, Dusit NiyatoTao Chen, Muhammad Khurram Khan, Abbas Jamalipour, Mohsen Guizani, Chau Yuen

*Corresponding author for this work

Research output: Contribution to journalReview Articlepeer-review

5 Citations (Scopus)

Abstract

With the growing demand for seamless connectivity and intelligent communication, the integration of artificial intelligence (AI) and sixth-generation (6G) communication networks has emerged as a transformative paradigm. By embedding AI capabilities across various network layers, this integration enables optimized resource allocation, improved efficiency, and enhanced system robust performance. This paper presents a comprehensive overview of AI and communication for 6G networks, with a focus on their foundational principles, inherent challenges, and future research opportunities. We first review the integration of AI and communications in the context of 6G, exploring the driving factors behind incorporating AI into wireless communications, as well as the vision for the convergence of AI and 6G. The discourse then transitions to a detailed exposition of the envisioned integration of AI within 6G networks, divided into three progressive stages. The first stage, AI for network, focuses on employing AI to augment network performance, optimize efficiency, and enhance user service experiences. The second stage, network for AI, highlights the role of the network in facilitating and buttressing AI operations and presents key enabling technologies. We compare wireless network large models with conventional large language models (LLMs), and identify key design principles and components for building wireless network architectures. In the final stage, AI as a service, it is anticipated that future 6G networks will innately provide AI functions as services, supporting application scenarios like immersive communication and intelligent industrial robots. Specifically, we define the quality of AI service, which refers to a framework for measuring AI services within the network. We further summarize the standardization process of AI for wireless networks, highlighting key milestones and ongoing efforts. In addition, we analyze the critical challenges faced by the integration of AI and communications in 6G. Finally, we outline promising future research opportunities that are expected to drive the development and refinement of AI and 6G communications.

Original languageEnglish
Article number171301
JournalScience China Information Sciences
Volume68
Issue number7
DOIs
Publication statusPublished - 2 Apr 2025
MoE publication typeA2 Review article in a scientific journal

Funding

This work was supported by Joint Funds for Regional Innovation and Development of National Natural Science Foundation of China (Grant No. U21A20449), Beijing Natural Science Foundation Program (Grant No. L232002), National Natural Science Foundation of China (Grant No. 62125108), National Key Research and Development Program of China (Grant No. 2020YFB1806804), and King Saud University, Riyadh, Saudi Arabia (Grant No. RSP2025R12).

Keywords

  • 6G
  • AI
  • AI and communication
  • AI as a service
  • AI for network
  • LLMs
  • network for AI

Fingerprint

Dive into the research topics of 'Overview of AI and communication for 6G network: fundamentals, challenges, and future research opportunities'. Together they form a unique fingerprint.

Cite this