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Improving the Spatial Reuse in IEEE 802.11ax WLANs: A Multi-Armed Bandit Approach

Published: 22 November 2021 Publication History

Abstract

The latest amendment 802.11ax to the IEEE 802.11 standard, better known by its commercial name Wi-Fi 6, includes a feature that aims at improving the spatial reuse of a channel: each device can adapt its Clear Channel Assessment sensitivity threshold and its transmission power. In this paper, we use the Multi-Armed Bandit (MAB) framework to propose a centralized solution to dynamically adapt these parameters. We propose a new approach based on a Gaussian mixture to sample new network configurations, a specific reward function that prevents starvations when maximized, as well as a method based on Thompson Sampling to select the best network configuration. We evaluate our solution using the network simulator ns-3 and different topologies. Simulation results confirm the large benefits that 802.11ax may bring to spatial reuse. They also demonstrate the efficiency of our solution in finding appropriate parameter configurations that significantly improve the quality of service of the networks.

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  • (2024)Cooperate or Not Cooperate: Transfer Learning With Multi-Armed Bandit for Spatial Reuse in Wi-FiIEEE Transactions on Machine Learning in Communications and Networking10.1109/TMLCN.2024.33719292(351-369)Online publication date: 2024
  • (2024)A Bayesian Optimization Algorithm to Improve the Spatial Reuse in the Next-Generation WLANs2024 International Wireless Communications and Mobile Computing (IWCMC)10.1109/IWCMC61514.2024.10592439(1048-1053)Online publication date: 27-May-2024
  • (2024)Enhancing Public Wi-Fi Accessibility and Coverage through NuttyFi ESP8266 Wi-Fi Module Extension2023 International Conference on Smart Devices (ICSD)10.1109/ICSD60021.2024.10751257(1-5)Online publication date: 2-May-2024
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cover image ACM Conferences
MSWiM '21: Proceedings of the 24th International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems
November 2021
251 pages
ISBN:9781450390774
DOI:10.1145/3479239
© 2021 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Publication History

Published: 22 November 2021

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Author Tags

  1. channel reuse
  2. clear channel assessment
  3. machine learning
  4. power control
  5. thompson sampling
  6. wlan

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Cited By

View all
  • (2024)Cooperate or Not Cooperate: Transfer Learning With Multi-Armed Bandit for Spatial Reuse in Wi-FiIEEE Transactions on Machine Learning in Communications and Networking10.1109/TMLCN.2024.33719292(351-369)Online publication date: 2024
  • (2024)A Bayesian Optimization Algorithm to Improve the Spatial Reuse in the Next-Generation WLANs2024 International Wireless Communications and Mobile Computing (IWCMC)10.1109/IWCMC61514.2024.10592439(1048-1053)Online publication date: 27-May-2024
  • (2024)Enhancing Public Wi-Fi Accessibility and Coverage through NuttyFi ESP8266 Wi-Fi Module Extension2023 International Conference on Smart Devices (ICSD)10.1109/ICSD60021.2024.10751257(1-5)Online publication date: 2-May-2024
  • (2023)Enhanced Coordinated Spatial Reuse: Bidirectional Multiple AP Coordination for IEEE 802.11beICC 2023 - IEEE International Conference on Communications10.1109/ICC45041.2023.10278896(660-665)Online publication date: 28-May-2023
  • (2023)Analysis of a decentralized Bayesian optimization algorithm for improving spatial reuse in dense WLANsComputer Communications10.1016/j.comcom.2023.06.004208(158-170)Online publication date: Aug-2023
  • (2023)Mitigating starvation in dense WLANsAd Hoc Networks10.1016/j.adhoc.2022.103015138:COnline publication date: 1-Jan-2023
  • (2022)A Survey of Wi-Fi 6: Technologies, Advances, and ChallengesFuture Internet10.3390/fi1410029314:10(293)Online publication date: 14-Oct-2022
  • (2022)Wi-Fi Meets ML: A Survey on Improving IEEE 802.11 Performance With Machine LearningIEEE Communications Surveys & Tutorials10.1109/COMST.2022.317924224:3(1843-1893)Online publication date: 1-Jul-2022
  • (2022)Analysis of a Multi-Armed Bandit solution to improve the spatial reuse of next-generation WLANsComputer Communications10.1016/j.comcom.2022.07.015193:C(279-292)Online publication date: 1-Sep-2022

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