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oai:recercat.cat:10230/716882025-10-30T00:44:17Zcom_2072_6col_2072_452952

Machine learning and Wi-Fi: unveiling the path toward AI/ML-Native IEEE 802.11 networks Wilhelmi Roca, Francesc Szott, Szymon Kosek-Szott, Katarzyna Bellalta, Boris Wireless fidelity Artificial intelligence IEEE 802.11 standard Computational modeling 3GPP Costs Standards Data models Protocols Computer architecture Machine learning 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. This paper is supported by the CHIST-ERA Wireless AI 2022 call MLDR project (ANR-23-CHR4-0005), partially funded by AEI and NCN under projects PCI2023-145958-2 and 2023/05/Y/ST7/00004, respectively. B. Bellalta's contribution is supported by Wi-XR PID2021-123995NB-I00 (MCIU/AEI/FEDER,UE) and MdM CEX2021-001195-M/AEI/10.13039/501100011033. 2025-10-29T09:25:39Z 2025-10-29T09:25:39Z 2025 2025-10-29T09:25:39Z info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Wilhelmi F, Szott S, Kosek-Szott K, Bellalta B. Machine learning and Wi-Fi: unveiling the path toward AI/ML-Native IEEE 802.11 networks. IEEE Commun Mag. 2025 Jul;63(7):114-20. DOI: 10.1109/MCOM.001.2400292 0163-6804 http://hdl.handle.net/10230/71688 http://dx.doi.org/10.1109/MCOM.001.2400292 http://hdl.handle.net/10230/71688 eng IEEE Communications Magazine. 2025 Jul;63(7):114-20 info:eu-repo/grantAgreement/ES/2PE/PID2021-123995NB-I00 info:eu-repo/grantAgreement/ES/3PE/PCI2023-145958-2 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/. http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess application/pdf application/pdf Institute of Electrical and Electronics Engineers (IEEE)