Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges

被引:143
|
作者
Wang, Cheng-Xiang [1 ,2 ]
Di Renzo, Marco [3 ]
Stanczak, Slawomir [4 ,5 ]
Wang, Sen [6 ]
Larsson, Erik G. [7 ]
机构
[1] Southeast Univ, Nanjing, Peoples R China
[2] Purple Mt Labs, Nanjing, Peoples R China
[3] Univ Paris Saclay, CNRS, Cent Supelec, Lab Signaux & Syst, Paris, France
[4] Heinrich Hertz Inst Nachrichtentech Berlin GmbH, Fraunhofer Inst Telecommun, Wireless Commun & Networks Dept, Berlin, Germany
[5] Tech Univ Berlin, Network Informat Theory, Berlin, Germany
[6] Heriot Watt Univ, Robot & Autonomous Syst, Edinburgh, Midlothian, Scotland
[7] Linkoping Univ, Linkoping, Sweden
基金
中国国家自然科学基金; 欧盟地平线“2020”; 国家重点研发计划;
关键词
Artificial intelligence; Channel estimation; Massive MIMO; 5G mobile communication; Loss measurement; Wireless networks; CHANNEL ESTIMATION;
D O I
10.1109/MWC.001.1900292
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
5G wireless communication networks are currently being deployed, and B5G networks are expected to be developed over the next decade. AI technologies and, in particular, ML have the potential to efficiently solve the unstructured and seemingly intractable problems by involving large amounts of data that need to be dealt with in B5G. This article studies how AI and ML can be leveraged for the design and operation of B5G networks. We first provide a comprehensive survey of recent advances and future challenges that result from bringing AI/ML technologies into B5G wireless networks. Our survey touches on different aspects of wireless network design and optimization, including channel measurements, modeling, and estimation, physical layer research, and network management and optimization. Then ML algorithms and applications to B5G networks are reviewed, followed by an overview of standard developments of applying AI/ML algorithms to B5G networks. We conclude this study with future challenges on applying AI/ML to B5G networks.
引用
收藏
页码:16 / 23
页数:8
相关论文
共 50 条
  • [41] Integration of Network and Artificial Intelligence toward the Beyond 5G/6G Networks
    Tagami, Atsushi
    Miyasaka, Takuya
    Suzuki, Masaki
    Sasaki, Chikara
    IEICE TRANSACTIONS ON COMMUNICATIONS, 2023, E106B (12) : 1267 - 1274
  • [42] 5G Wireless Access of the Future
    Dahlman, Erik
    2017 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXHIBITION (OFC), 2017,
  • [43] The role of unmanned aerial vehicles and mmWave in 5G: Recent advances and challenges
    Khan, Shah Khalid
    Naseem, Usman
    Siraj, Haris
    Razzak, Imran
    Imran, Muhammad
    TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES, 2021, 32 (07):
  • [44] Artificial intelligence in 5G and 6G
    Laselva, Sarah
    Electronics World, 2024, 129 (2033): : 16 - 17
  • [45] Packet Duplication in Dual Connectivity Enabled 5G Wireless Networks: Overview and Challenges
    Aijaz A.
    IEEE Communications Standards Magazine, 2019, 3 (03): : 20 - 28
  • [46] Dynamic Spectrum Sharing in 5G Wireless Networks With Full-Duplex Technology: Recent Advances and Research Challenges
    Sharma, Shree Krishna
    Bogale, Tadilo Endeshaw
    Le, Long Bao
    Chatzinotas, Symeon
    Wang, Xianbin
    Ottersten, Bjoern
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2018, 20 (01): : 674 - 707
  • [47] Fixed Wireless Transport Technologies in the 5G and Beyond 5G Eras
    Ogawa, Takatoshi
    Sonobe, Satoshi
    NEC Technical Journal, 2023, 17 (01): : 178 - 181
  • [48] Editorial: special issue on "artificial intelligence for future wireless communications and networking"
    Tony, Q. S.
    Tang, Jianhua
    Wang, Jian
    Feng, Gang
    DIGITAL COMMUNICATIONS AND NETWORKS, 2019, 5 (01) : 1 - 2
  • [49] Artificial Intelligence in 5G Technology: A Survey
    Cayamcela, Manuel Eugenio Morocho
    Lim, Wansu
    2018 INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE (ICTC), 2018, : 860 - 865
  • [50] Interference Management in 5G and Beyond Network: Requirements, Challenges and Future Directions
    Siddiqui, Maraj Uddin Ahmed
    Qamar, Faizan
    Ahmed, Faisal
    Nguyen, Quang Ngoc
    Hassan, Rosilah
    IEEE ACCESS, 2021, 9 : 68932 - 68965