AGILE: Intelligent Prioritized Low-Latency Channel Access for Next Generation Wi-Fi 8

• Juseong Moon,
• Gwangho Lee,
• Ronny Yongho Kim,

Vol. 20, No. 2, February 28, 2026
10.3837/tiis.2026.02.020, Download Paper (Free):

• Wi-Fi 8
• IEEE 802.11bn
• Enhanced Distributed Channel Access
• Low-latency
• deep reinforced learning

Abstract

IEEE 802.11bn (Wi-Fi 8) is under development as the 8th-generation Ultra High Reliability (UHR) WLAN standard, targeting high reliability and ultra-low latency. To support such demands, the IEEE 802.11 Task Group (TG) bn has proposed Prioritized Enhanced Distributed Channel Access (P-EDCA), an extension of legacy Enhanced Distributed Channel Access (EDCA). However, P-EDCA suffers from contention collisions with legacy EDCA users due to shared channel access slot duration settings, limiting its effectiveness. This paper presents AGILE, a simple yet effective enhancement to P-EDCA that introduces a Differentiated AIFS Length Adjustment mechanism. By adjusting arbitrary interframe space (AIFS) length between P-EDCA and legacy EDCA stations, AGILE reduces latency tail for low-latency traffic or improves fairness in mixed network environments. Simulation results demonstrate that AGILE significantly enhances latency performance and collision avoidance under various traffic loads, without sacrificing compatibility with existing standards. Furthermore, this paper introduces AGILE-Q, a deep reinforcement learning based extension of AGILE that adaptively selects P-EDCA operating modes according to dynamic traffic and collision conditions, enabling adaptive low-latency performance in diverse environments.

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