On the Analysis of Computational Delays in Reinforcement Learning-Based Rate Adaptation Algorithms-Reference-Cited by-同舟云学术

On the Analysis of Computational Delays in Reinforcement Learning-Based Rate Adaptation Algorithms

Published:2024 Issue: Volume: Page:299-310
ISSN:1867-8211
Container-title:Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
language:en
Short-container-title:

Author:

Trancoso Ricardo^ORCID,Pinto João,Queiros Ruben^ORCID,Fontes Helder^ORCID,Campos Rui^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-57523-5_23

Reference13 articles.

1. IEEE standard for information technology–telecommunications and information exchange between systems local and metropolitan area networks–specific requirements part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications amendment 1: Enhancements for high-efficiency WLAN. IEEE Std. 802.11ax-2021 (Amendment to IEEE Std. 802.11-2020), pp. 1–767 (2021). https://doi.org/10.1109/IEEESTD.2021.9442429

2. The minstrel rate control algorithm for mac80211. https://wireless.wiki.kernel.org/en/developers/documentation/mac80211/ratecontrol/minstrel. Accessed 1 Feb 2022

3. Grünblatt, R., Guérin-Lassous, I., Simonin, O.: Simulation and performance evaluation of the Intel rate adaptation algorithm. MSWiM (2019). https://doi.org/10.1145/3345768.3355921

4. Chen, S.C., Li, C.Y., Chiu, C.H.: An experience driven design for IEEE 802.11ac rate adaptation based on reinforcement learning. In: IEEE INFOCOM 2021 (2021). https://doi.org/10.1109/infocom42981.2021.9488876

5. Karmakar, R., Chattopadhyay, S., Chakraborty, S.: SmartLA: reinforcement learning-based link adaptation for high throughput wireless access networks. Comput. Commun. (2017). https://doi.org/10.1016/j.comcom.2017.05.017