Machine Learning and Wi-Fi: Unveiling the Path Toward AI/ML-Native IEEE 802.11 Networks

Artificial intelligence (AI) and machine learning (ML) are nowadays mature technologies considered essential for driving the evolution of future communications systems. Simultaneously, Wi-Fi technology has constantly evolved over the past three decades and incorporated new features generation after generation, thus gaining in complexity. As such, researchers have observed that AI/ML functionalities may be required to address the upcoming Wi-Fi challenges that will be otherwise difficult to solve with traditional approaches. This article discusses the role of AI/ML in current and future Wi-Fi networks, and depicts the ways forward. A roadmap toward AI/ML-native Wi-Fi, key challenges, standardization efforts, and major enablers are also discussed. An exemplary use case is provided to showcase the potential of AI/ML in Wi-Fi at different adoption stages.

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Institutions

Publication Details

Journal
IEEE Communications Magazine
Published
2024-10-22
DOI
https://doi.org/10.1109/mcom.001.2400292
Citations
8
Primary Topic
Wireless Body Area Networks
Type
article
Field-Weighted Citation Impact
1.48

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article

Machine Learning and Wi-Fi: Unveiling the Path Toward AI/ML-Native IEEE 802.11 Networks

Szymon Szott, Katarzyna Kosek‐Szott, Francesc Wilhelmi, Boris Bellalta
8 citations
IEEE Communications Magazine
Wireless Body Area Networks
1.48
article

Machine Learning and Wi-Fi: Unveiling the Path Toward AI/ML-Native IEEE 802.11 Networks

Szymon Szott, Katarzyna Kosek‐Szott, Francesc Wilhelmi, Boris Bellalta
article en
8 citations

Abstract

Artificial intelligence (AI) and machine learning (ML) are nowadays mature technologies considered essential for driving the evolution of future communications systems. Simultaneously, Wi-Fi technology has constantly evolved over the past three decades and incorporated new features generation after generation, thus gaining in complexity. As such, researchers have observed that AI/ML functionalities may be required to address the upcoming Wi-Fi challenges that will be otherwise difficult to solve with traditional approaches. This article discusses the role of AI/ML in current and future Wi-Fi networks, and depicts the ways forward. A roadmap toward AI/ML-native Wi-Fi, key challenges, standardization efforts, and major enablers are also discussed. An exemplary use case is provided to showcase the potential of AI/ML in Wi-Fi at different adoption stages.

IEEE Communications MagazineVol. 63(7)
Jagiellonian University (PL), Universitat Pompeu Fabra (ES), Nokia (Germany) (DE), AGH University of Krakow (PL)
Ministerio de Ciencia, Innovación y Universidades, Agence Nationale de la Recherche, Agencia Estatal de Investigación, CHIST-ERA
Openalex Percentile: Top 19%
Wireless Body Area Networks
1.48
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