The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges
Open accessAbstract
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.
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Citations
Cites
Deep Learning-Based Channel Estimation for Beamspace mmWave Massive MIMO Systems
He, H., Wen, C.-K., Jin, S., & Li, G. Y. (2018) · IEEE Wireless Communications Letters · doi:10.1109/lwc.2018.2832128 · Cited by 823
Cited by
The Role of Millimeter-Wave Technologies in 5G/6G Wireless Communications
Hong, W., Jiang, Z. H., Yu, C., Hou, D., Wang, H., Guo, C., Hu, Y., Kuai, L., Yu, Y., Jiang, Z., et al. (2021) · IEEE Journal of Microwaves · doi:10.1109/jmw.2020.3035541 · Cited by 915
Multi-agent deep reinforcement learning based resource management in heterogeneous V2X networks
Zhao, J., Hu, F., Li, J., & Nie, Y. (2025) · Digital Communications and Networks · doi:10.1016/j.dcan.2023.06.003 · Cited by 21
Metadata
- Authors
- Wang, C.-X., Renzo, M. D., Stanczak, S., Wang, S., & Larsson, E. G.
- Venue
- IEEE Wireless Communications
- Published
- 2020-02
- Volume
- 27
- Issue
- 1
- Pages
- 16-23
- ISSN
- 1536-1284 (ISSN-L)
- 1558-0687
- OpenAlex
- W3010109240
- Cited by
- 313
- References
- 1
- FWCI
- 13.33
- Type
- journal article
- Language
- en
- Open access
- green
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- Wang, C.-X., Renzo, M. D., Stanczak, S., Wang, S., & Larsson, E. G. (2020). Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges. IEEE Wireless Communications. https://doi.org/10.1109/mwc.001.1900292
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