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Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges (2001.08159v1)

Published 2 Jan 2020 in cs.NI and eess.SP

Abstract: The fifth generation (5G) wireless communication networks are currently being deployed, and beyond 5G (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 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 by the future challenges on applying AI/ML to B5G networks.

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Authors (5)
  1. Cheng-Xiang Wang (97 papers)
  2. Marco Di Renzo (257 papers)
  3. Sen Wang (165 papers)
  4. Erik G. Larsson (252 papers)
  5. Slawomir StaƄczak (4 papers)
Citations (153)

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