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
  • [31] Contours of Future Directions for Geographic Study of 6G Wireless Communications
    Blanutsa V.I.
    Regional Research of Russia, 2024, 14 (1) : 98 - 107
  • [32] Secure Artificial Intelligence for Precise Vehicle Behavior Prediction in 6G Consumer Electronics
    Haider, Sami Ahmed
    Ramesh, Janjhyam Venkata Naga
    Raina, Vikas
    Maaliw III, Renato R.
    Soni, Mukesh
    Nasurova, Kamolakhon
    Patni, Jagdish Chandra
    Singh, Pavitar Parkash
    IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2024, 70 (01) : 3898 - 3905
  • [33] Artificial Intelligence Augmentation for Channel State Information in 5G and 6G
    Li, Yang
    Hu, Yeqing
    Min, Kyungsik
    Park, HyoYol
    Yang, Hayoung
    Wang, Tiexing
    Sung, Junmo
    Seol, Ji-Yun
    Zhang, Charlie Jianzhong
    IEEE WIRELESS COMMUNICATIONS, 2023, 30 (01) : 104 - 110
  • [34] Knowledge-Driven Deep Learning Paradigms for Wireless Network Optimization in 6G
    Sun, Ruijin
    Cheng, Nan
    Li, Changle
    Chen, Fangjiong
    Chen, Wen
    IEEE NETWORK, 2024, 38 (02): : 70 - 78
  • [35] Augmented Artificial Intelligence in 5G, 6G, and Beyond: A Quantum Leap
    Sinha, Saurabh
    Lambrechts, J. Wynand
    Bimana, Aba
    Ashipala, Aili
    COMPUTER, 2025, 58 (01) : 24 - 32
  • [36] AI Models for Green Communications Towards 6G
    Mao, Bomin
    Tang, Fengxiao
    Kawamoto, Yuichi
    Kato, Nei
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2022, 24 (01): : 210 - 247
  • [37] Toward immersive communications in 6G
    Shen, Xuemin
    Gao, Jie
    Li, Mushu
    Zhou, Conghao
    Hu, Shisheng
    He, Mingcheng
    Zhuang, Weihua
    FRONTIERS IN COMPUTER SCIENCE, 2023, 4
  • [38] Enabling 6G Security: The Synergy of Zero Trust Architecture and Artificial Intelligence
    Sedjelmaci, Hichem
    Tourki, Kamel
    Ansari, Nirwan
    IEEE NETWORK, 2024, 38 (03): : 171 - 177
  • [39] Explainable Artificial Intelligence for 6G: Improving Trust between Human and Machine
    Guo, Weisi
    IEEE COMMUNICATIONS MAGAZINE, 2020, 58 (06) : 39 - 45
  • [40] Qualitative Survey on Artificial Intelligence Integrated Blockchain Approach for 6G and Beyond
    Pathak, Vivek
    Pandya, Rahul Jashvantbhai
    Bhatia, Vimal
    Lopez, Onel Alcaraz
    IEEE ACCESS, 2023, 11 : 105935 - 105981