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October 20, 2025Open Access

AI-Enhanced Distributed Channel Access for Collision Avoidance in Future Wi-Fi 8

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Authors

JPJiahui PanChinese University of Hong KongJWJingqing WangXidian UniversityYOYuehui Ouyang

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Overview

This paper presents AI-driven solutions for collision avoidance and fairness in Wi-Fi 8, optimizing distributed channel access methods.

Key Points

  • The proposed system significantly reduces collision probability in Wi-Fi networks, enhancing overall performance.
  • Utilizing multi-agent reinforcement learning, the method adapts to real-time channel conditions while ensuring compatibility.
  • A new fairness quantification metric is introduced to provide equitable access opportunities across devices.
  • Results show effective minimization of collisions and elimination of starvation risks in diverse deployment scenarios.

Cite This Study

Pan et al. (2025) studied this question.

synapsesocial.com/papers/68f6196ee0bbbc94fac3650chttps://doi.org/10.48550/arxiv.2509.23154
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  1. 1Federated Deep Reinforcement Learning-Based Intelligent Channel Access in Dense Wi-Fi Deployments2024
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