Szczegóły publikacji
Opis bibliograficzny
Coordinated spatial reuse scheduling with machine learning in IEEE 802.11 MAPC networks / Maksymilian WOJNAR, Wojciech CIĘŻOBKA, Artur Tomaszewski, Piotr CHOŁDA, Krzysztof RUSEK, Katarzyna KOSEK-SZOTT, Jetmir Haxhibeqiri, Jeroen Hoebeke, Boris Bellalta, Anatolij Zubow, Falko Dressler, Szymon SZOTT // IEEE Journal on Selected Areas in Communications ; ISSN 0733-8716 . — 2025 — vol. 43 no. 11, s. 3666-3682. — Bibliogr. s. 3680-3681, Abstr. — Publikacja dostępna online od: 2025-07-02
Autorzy (12)
- AGHWojnar Maksymilian
- AGHCiężobka Wojciech
- Tomaszewski Artur
- AGHChołda Piotr
- AGHRusek Krzysztof
- AGHKosek-Szott Katarzyna
- Haxhibeqiri Jetmir
- Hoebeke Jeroen
- Bellalta Boris
- Zubow Anatolij
- Dressler Falko
- AGHSzott Szymon
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 164250 |
|---|---|
| Data dodania do BaDAP | 2025-11-14 |
| Tekst źródłowy | URL |
| DOI | 10.1109/JSAC.2025.3584555 |
| Rok publikacji | 2025 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | IEEE Journal on Selected Areas in Communications |
Abstract
The densification of Wi-Fi deployments means that fully distributed random channel access is no longer sufficient for high and predictable performance. Therefore, the upcoming IEEE 802.11bn amendment introduces multi-access point coordination (MAPC) methods. This paper addresses a variant of MAPC called coordinated spatial reuse (C-SR), where devices transmit simultaneously on the same channel, with the power adjusted to minimize interference. The C-SR scheduling problem is selecting which devices transmit concurrently and with what settings. We provide a theoretical upper bound model, optimized for either throughput or fairness, which finds the best possible transmission schedule using mixed-integer linear programming. Then, a practical, probing-based approach is proposed which uses multi-armed bandits (MABs), a type of reinforcement learning, to solve the C-SR scheduling problem. We validate both classical (flat) MAB and hierarchical MAB (H-MAB) schemes with simulations and in a testbed. Using H-MABs for C-SR improves aggregate throughput over legacy IEEE 802.11 (on average by 80% in random scenarios), without reducing the number of transmission opportunities per station. Finally, our framework is lightweight and ready for implementation in Wi-Fi devices.
