Realtime intelligent control for NextG cellular radio access networks
Pages 567 - 568
Abstract
RAN Intelligent Control (RIC) has developed in parallel with Open Radio Access Networks (O-RAN) as a means of utilizing newly available interfaces. Focus has been largely on non-realtime (non-RT: > 1 sec) dealing with RAN management and offline training, and near-realtime (near-RT: 10 ms to 1 sec) dealing with UE load balancing and RAN configuration. We contend that the true power of RIC can be unleashed only with realtime (RT: < 100 μs) measurement, optimization, and control of RAN resources, corresponding to the cellular transmission time interval (TTI: 125 μs to 1 ms).
References
[1]
"srsRAN, Inc." https://www.srslte.com/, 2021.
[2]
L. Bonati, S. D'Oro, S. Basagni, and T. Melodia, "SCOPE: An open and softwarized prototyping platform for NextG systems," in Proceedings of MobiSys, 2021.
[3]
L. Baldesi, F. Restuccia, and T. Melodia, "ChARM: NextG spectrum sharing through data-driven real-time O-RAN dynamic control," arXiv:2201.06326, 2022.
[4]
"OpenAIGym," https://gym.openai.com/, 2022.
[5]
J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov, "Proximal policy optimization algorithms," arXiv preprint arXiv:1707.06347, 2017.
Index Terms
- Realtime intelligent control for NextG cellular radio access networks
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Published In
June 2022
668 pages
ISBN:9781450391856
DOI:10.1145/3498361
- General Chairs:
- Nirupama Bulusu,
- Ehsan Aryafar,
- Program Chairs:
- Aruna Balasubramanian,
- Junehwa Song
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 27 June 2022
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MobiSys '22: The 20th Annual International Conference on Mobile Systems, Applications and Services
June 27 - July 1, 2022
Oregon, Portland
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Overall Acceptance Rate 274 of 1,679 submissions, 16%
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