IEEE 802.11bn Multi-AP Coordinated Spatial Reuse With Hierarchical Multi-Armed Bandits
Coordination among multiple access points (APs) is integral to IEEE 802.11bn (Wi-Fi 8) for managing contention in dense networks. This letter explores the benefits of Coordinated Spatial Reuse (C-SR) and proposes the use of reinforcement learning to optimize C-SR group selection. We develop a hierarchical multi-armed bandit (MAB) framework that efficiently selects APs for simultaneous transmissions across various network topologies, demonstrating reinforcement learning’s promise in Wi-Fi settings. Among several MAB algorithms studied, we identify the upper confidence bound (UCB) as particularly effective, offering rapid convergence, adaptability to changes, and sustained performance.
Authors
- Szymon Szott (ORCID: https://orcid.org/0000-0001-5884-5581)
- Krzysztof Rusek (ORCID: https://orcid.org/0000-0003-4336-7841)
- Katarzyna Kosek‐Szott (ORCID: https://orcid.org/0000-0001-7609-9420)
- Wojciech Ciężobka (ORCID: https://orcid.org/0000-0003-2972-710X)
- Boris Bellalta (ORCID: https://orcid.org/0000-0002-7826-3703)
- Maksymilian Wojnar (ORCID: https://orcid.org/0000-0003-4510-5976)
- David Nunez
Institutions
- Jagiellonian University (PL)
- FC Barcelona (ES)
- AGH University of Krakow (PL)
Publication Details
- Journal
- IEEE Communications Letters
- Published
- 2024-12-23
- DOI
- https://doi.org/10.1109/lcomm.2024.3521079
- Citations
- 6
- Primary Topic
- Advanced Bandit Algorithms Research
- Type
- article
- Field-Weighted Citation Impact
- 2.94
Funders
- Ministerio de Ciencia, Innovación y Universidades
- Narodowe Centrum Nauki
- Narodowym Centrum Nauki
- Agencia Estatal de Investigación