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

Cheng-Xiang Wang, Marco Di Renzo, Slawomir Stanczak, Sen Wang, Erik G. Larsson

Research output: Contribution to journalArticlepeer-review

136 Citations (Scopus)
122 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)16-23
Number of pages8
JournalIEEE Wireless Communications
Issue number1
Publication statusPublished - Feb 2020

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering


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