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Sökning: id:"swepub:oai:DiVA.org:liu-164860" > Artificial Intellig...

  • Wang, Cheng-XiangSoutheast Univ, Peoples R China; Purple Mt Labs, Peoples R China (författare)

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

  • Artikel/kapitelEngelska2020

Förlag, utgivningsår, omfång ...

  • IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC,2020
  • electronicrdacarrier

Nummerbeteckningar

  • LIBRIS-ID:oai:DiVA.org:liu-164860
  • https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-164860URI
  • https://doi.org/10.1109/MWC.001.1900292DOI

Kompletterande språkuppgifter

  • Språk:engelska
  • Sammanfattning på:engelska

Ingår i deldatabas

Klassifikation

  • Ämneskategori:ref swepub-contenttype
  • Ämneskategori:art swepub-publicationtype

Anmärkningar

  • Funding Agencies|National Key R&D Program of China [2018YFB1801101]; National Natural Science Foundation of China (NSFC)National Natural Science Foundation of China [61960206006]; High Level Innovation and Entrepreneurial Talent Introduction Program in Jiangsu; Research Fund of National Mobile Communications Research Laboratory, Southeast University [2020B01]; Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities [2242019R30001]; EU H2020 RISE TESTBED2 project [872172]
  • 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.

Ämnesord och genrebeteckningar

Biuppslag (personer, institutioner, konferenser, titlar ...)

  • Di Renzo, MarcoUniv Paris Saclay, France (författare)
  • Stanczak, SlawomirHeinrich Hertz Inst Nachrichtentech Berlin GmbH, Germany; Tech Univ Berlin, Germany (författare)
  • Wang, SenHeriot Watt Univ, Scotland (författare)
  • Larsson, Erik GLinköpings universitet,Kommunikationssystem,Tekniska fakulteten(Swepub:liu)erila39 (författare)
  • Southeast Univ, Peoples R China; Purple Mt Labs, Peoples R ChinaUniv Paris Saclay, France (creator_code:org_t)

Sammanhörande titlar

  • Ingår i:IEEE wireless communications: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC27:1, s. 16-231536-12841558-0687

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