This is the homepage for the paper "Coordinated Spatial Reuse Scheduling with Machine Learning in IEEE 802.11 MAPC Networks".
The paper presents results obtained using the following code:
- upper bound C-SR model - a theoretical model of C-SR, which finds the best possible transmission schedule using mixed-integer linear programming,
- DCF and SR simulator - a discrete event simulator (built using SimPy), in which devices use either legacy IEEE 802.11 channel access (DCF) or 802.11ax spatial reuse (SR),
- C-SR simulator - a Monte Carlo simulator of consecutive C-SR transmission opportunities,
- H-MAB framework - our hierarchical multi-armed bandit framework to determine C-SR scheduling,
- scripts and scenarios - the main repository comprising installation instructions and a set of simulation scenarios (including implementations and definitions) to validate IEEE 802.11 performance under the various channel access schemes and scripts to run these simulations.
Other relevant links:
- figures - figures illustrating the obtained results,
- raw simulation results, #TODO add link
- openwifi - openwifi repository used in the experimental testbed.
@article{wojnar2025coordinated,
author={Wojnar, Maksymilian and Ciężobka, Wojciech and Tomaszewski, Artur and Chołda, Piotr and Rusek, Krzysztof and Kosek-Szott, Katarzyna and Haxhibeqiri, Jetmir and Hoebeke, Jeroen and Bellalta, Boris and Zubow, Anatolij and Dressler, Falko and Szott, Szymon},
title={{Coordinated Spatial Reuse Scheduling With Machine Learning in IEEE 802.11 MAPC Networks}},
year={2025},
}