skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

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

IEEE wireless communications, 2020-02, Vol.27 (1), p.16 [Peer Reviewed Journal]

ISSN: 1558-0687 ;ISSN: 1536-1284 ;EISSN: 1558-0687 ;DOI: 10.1109/MWC.001.1900292

Digital Resources/Online E-Resources

Citations Cited by
  • Title:
    Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges
  • Author: Wang, Cheng-Xiang ; Di Renzo, Marco ; Stanczak, Slawomir ; Wang, Sen ; Larsson, Erik G
  • Is Part Of: IEEE wireless communications, 2020-02, Vol.27 (1), p.16
  • Description: 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.
  • Language: English
  • Identifier: ISSN: 1558-0687
    ISSN: 1536-1284
    EISSN: 1558-0687
    DOI: 10.1109/MWC.001.1900292
  • Source: SWEPUB Freely available online

Searching Remote Databases, Please Wait