Crowding Game and Deep Q-Networks for Dynamic RAN Slicing in 5G Networks-Reference-Cited by-同舟云学术

Crowding Game and Deep Q-Networks for Dynamic RAN Slicing in 5G Networks

Published:2022-10-24 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 20th ACM International Symposium on Mobility Management and Wireless Access on 20th ACM International Symposium on Mobility Management and Wireless Access
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Author:

Saad Joe¹,Khawam Kinda²,Yassin Mohamad³,Costanzo Salvatore³,Boulos Karen³

Affiliation:

1. University of Versailles & Orange Labs, Versailles, France

2. University of Versailles, Versailles, France

3. Orange Labs, Châtillon, France

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3551660.3560908

Reference28 articles.

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2. Dynamic Slicing of RAN Resources for Heterogeneous Coexisting 5G Services

3. Thomas Bonald and James W Roberts . 2003. Congestion at flow level and the impact of user behaviour. Computer networks 42, 4 ( 2003 ), 521--536. Thomas Bonald and James W Roberts. 2003. Congestion at flow level and the impact of user behaviour. Computer networks 42, 4 (2003), 521--536.

4. Leonardo Bonati , Salvatore D'Oro , Michele Polese , Stefano Basagni , and Tommaso Melodia . 2020. Intelligence and Learning in O-RAN for Data-driven NextG Cellular Networks. arXiv preprint arXiv:2012.01263 ( 2020 ). Leonardo Bonati, Salvatore D'Oro, Michele Polese, Stefano Basagni, and Tommaso Melodia. 2020. Intelligence and Learning in O-RAN for Data-driven NextG Cellular Networks. arXiv preprint arXiv:2012.01263 (2020).

5. A Crowding Game for Dynamic RAN Slicing Algorithm in 5G Networks

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