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Realtime intelligent control for NextG cellular radio access networks

Published: 27 June 2022 Publication History

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.

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cover image ACM Conferences
MobiSys '22: Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services
June 2022
668 pages
ISBN:9781450391856
DOI:10.1145/3498361
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 27 June 2022

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  1. RAN intelligent control
  2. reinforcement learning

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Overall Acceptance Rate 274 of 1,679 submissions, 16%

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