mlsanityData to 14 Oct 2026

What Will Wi-Fi 8 Be? A Primer on IEEE 802.11bn Ultra High Reliability

arXiv 2303.10442 ↗First posted 18 Mar 2023cs.NI cs.IT eess.SPcited by 10

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Abstract (arXiv)

What will Wi-Fi 8 be? Driven by the strict requirements of emerging applications, next-generation Wi-Fi is set to prioritize Ultra High Reliability (UHR) above all. In this paper, we explore the journey towards IEEE 802.11bn UHR, the amendment that will form the basis of Wi-Fi 8. We first present new use cases calling for further Wi-Fi evolution and associated standardization, certification, and spectrum allocation efforts. We then introduce a selection of the main disruptive features envisioned for Wi-Fi 8 and their associated research challenges, resulting from the outcome of the UHR Study Group. Among those, we focus on multi access point coordination and demonstrate that it could build upon 802.11be multi-link operation to make UHR a reality in Wi-Fi 8.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Mar 2023.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 4; 2025: 3; 2026: 1.

10 papers.

  1. 2023AI/ML-based Load Prediction in IEEE 802.11 Enterprise Networkscited by 3
  2. 2024ML Framework for Wireless MAC Protocol Designcited by 2
  3. 2025Learning Multi-Access Point Coordination in Agentic AI Wi-Fi with Large Language Modelscited by 2
  4. 2023A Federated Reinforcement Learning Framework for Link Activation in Multi-link Wi-Fi Networkscited by 1
  5. 2024Distributed Learning for Wi-Fi AP Load Predictioncited by 1
  6. 2024MAC Revivo: Artificial Intelligence Paves the Waycited by 1
  7. 2024On the Accuracy and Precision of Moving Averages to Estimate Wi-Fi Link Qualitycited by 0
  8. 2025Accurate and Efficient Prediction of Wi-Fi Link Quality Based on Machine Learningcited by 0
  9. 2025AI-Enhanced Distributed Channel Access for Collision Avoidance in Future Wi-Fi 8cited by 0
  10. 2026An Informativeness-based Clustered Federated Learning Method for Reliable Traffic Prediction in Managed Wi-Fi Networkscited by 0