Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs

Francesc Wilhelmi; Jernej Hribar; Selim F. Yilmaz; Emre Ozfatura; Kerem Ozfatura; Ozlem Yildiz; Deniz Gündüz; Hao Chen; Xiaoying Ye; Lizhao You; Yulin Shao; Paolo Dini; Boris Bellalta

Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs

Networking and Internet Architecture 2022-06-08 v2 Artificial Intelligence Distributed, Parallel, and Cluster Computing Machine Learning

Authors: Francesc Wilhelmi , Jernej Hribar , Selim F. Yilmaz , Emre Ozfatura , Kerem Ozfatura , Ozlem Yildiz , Deniz Gündüz , Hao Chen , Xiaoying Ye , Lizhao You , Yulin Shao , Paolo Dini , Boris Bellalta

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Abstract

As wireless standards evolve, more complex functionalities are introduced to address the increasing requirements in terms of throughput, latency, security, and efficiency. To unleash the potential of such new features, artificial intelligence (AI) and machine learning (ML) are currently being exploited for deriving models and protocols from data, rather than by hand-programming. In this paper, we explore the feasibility of applying ML in next-generation wireless local area networks (WLANs). More specifically, we focus on the IEEE 802.11ax spatial reuse (SR) problem and predict its performance through federated learning (FL) models. The set of FL solutions overviewed in this work is part of the 2021 International Telecommunication Union (ITU) AI for 5G Challenge.

Keywords

federated learning network protocol

Cite

@article{arxiv.2203.10472,
  title  = {Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs},
  author = {Francesc Wilhelmi and Jernej Hribar and Selim F. Yilmaz and Emre Ozfatura and Kerem Ozfatura and Ozlem Yildiz and Deniz Gündüz and Hao Chen and Xiaoying Ye and Lizhao You and Yulin Shao and Paolo Dini and Boris Bellalta},
  journal= {arXiv preprint arXiv:2203.10472},
  year   = {2022}
}

Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs

Abstract

Keywords

Cite

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