Nine Challenges in Artificial Intelligence and Wireless Communications for 6G

被引:62
作者
Tong, Wen [1 ]
Li, Geoffrey Ye [2 ]
机构
[1] Huawei Technol, Markham, ON, Canada
[2] Imperial Coll London, London, England
关键词
Artificial intelligence; Biological neural networks; Neural networks; 6G mobile communication; Deep learning; Wireless networks; Data models;
D O I
10.1109/MWC.006.2100543
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, artificial intelligence (AI) techniques, especially machine learning (ML), have been successfully applied in various areas, leading to a widespread belief that AI will collectively play an important role in future wireless communications. To accomplish the aspiration, we present nine challenges to be addressed by the interdisciplinary areas of AI/ML and wireless communications, with particular focus on the sixth generation (6G) wireless networks. Specifically, this article classifies the nine challenges into computation in AI, distributed neural networks and learning, and semantic communications.
引用
收藏
页码:140 / 145
页数:6
相关论文
共 50 条
  • [1] A Survey of Blockchain and Artificial Intelligence for 6G Wireless Communications
    Zuo, Yiping
    Guo, Jiajia
    Gao, Ning
    Zhu, Yongxu
    Jin, Shi
    Li, Xiao
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2023, 25 (04): : 2494 - 2528
  • [2] Towards artificial intelligence enabled 6G: State of the art, challenges, and opportunities
    Zhang, Shunliang
    Zhu, Dali
    COMPUTER NETWORKS, 2020, 183 (183)
  • [3] The Convergence of Artificial Intelligence Foundation Models and 6G Wireless Communication Networks
    Shoaib, Mohamed R.
    Wang, Zefan
    Zhao, Jun
    2024 IEEE 99TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2024-SPRING, 2024,
  • [4] Artificial intelligence for channel estimation in multicarrier systems for B5G/6G communications: a survey
    Boas, Evandro C. Vilas C.
    S. e Silva, Jefferson D. S.
    de Figueiredo, Felipe A. P.
    Mendes, Luciano L. L.
    de Souza, Rausley A. A.
    EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2022, 2022 (01)
  • [5] Artificial intelligence for channel estimation in multicarrier systems for B5G/6G communications: a survey
    Evandro C. Vilas Boas
    Jefferson D. S. e Silva
    Felipe A. P. de Figueiredo
    Luciano L. Mendes
    Rausley A. A. de Souza
    EURASIP Journal on Wireless Communications and Networking, 2022
  • [6] Learning IoV in 6G: Intelligent Edge Computing for Internet of Vehicles in 6G Wireless Communications
    Li, He
    Ota, Kaoru
    Dong, Mianxiong
    IEEE WIRELESS COMMUNICATIONS, 2023, 30 (06) : 96 - 101
  • [7] 6G: THE PARADIGM FOR FUTURE WIRELESS COMMUNICATIONS
    Mumtaz, Shahid
    Jiang, Chunxiao
    Tolli, Antti
    Al-Dulaimi, Anwer
    Butt, M. Majid
    Asif, Hafiz M.
    Ashraf, Muhammad Ikram
    IEEE WIRELESS COMMUNICATIONS, 2022, 29 (01) : 14 - 15
  • [8] 6G Wireless Communications and Artificial Intelligence-Controlled Reconfigurable Intelligent Surfaces: From Supervised to Federated Learning
    Zaoutis, Evangelos A.
    Liodakis, George S.
    Baklezos, Anargyros T.
    Nikolopoulos, Christos D.
    Ioannidou, Melina P.
    Vardiambasis, Ioannis O.
    APPLIED SCIENCES-BASEL, 2025, 15 (06):
  • [9] 6G Wireless with Cyber Care and Artificial Intelligence for Patient Data Prediction
    Alshammari, Abdullah
    Innab, Nisreen
    Zayani, Hafedh Mahmoud
    Shutaywi, Meshal
    Alroobaea, Roobaea
    Deebani, Wejdan
    Almutairi, Laila
    WIRELESS PERSONAL COMMUNICATIONS, 2024,
  • [10] Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges
    Al-Quraan, Mohammad
    Mohjazi, Lina
    Bariah, Lina
    Centeno, Anthony
    Zoha, Ahmed
    Arshad, Kamran
    Assaleh, Khaled
    Muhaidat, Sami
    Debbah, Merouane
    Ali Imran, Muhammad
    IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE, 2023, 7 (03): : 957 - 979