🤖 AI Summary
This study addresses the challenges of integrating communication, sensing, and computing in Wi-Fi 9 (IEEE 802.11bx) by exploring technical pathways toward AI-ready wireless networks. It proposes an analytical framework for AI integration spanning three dimensions: protocol, platform, and traffic. Furthermore, a differentiated processing scheme for AI traffic is designed based on an extended Enhanced Distributed Channel Access (EDCA) mechanism. This work systematically reviews recent optimization advances within the IEEE 802.11 standard at both the PHY and MAC layers, delineating a clear evolutionary roadmap for AI-ready Wi-Fi 9. Ultimately, this research provides a theoretical framework and technical reference for achieving native AI support in next-generation wireless local area networks.
📝 Abstract
Wi-Fi 9 is expected to go beyond mere communication and provide new services such as sensing or computation. At this juncture, Artificial Intelligence (AI) is taking a leading role in the definition of the 802.11bx amendment, named WLAN Intelligent Networking (WIN). In this tutorial, we survey the recent progress made toward Wi-Fi 9 within IEEE 802.11 standardization, tracing the drivers and technological advances that motivate an AI-ready Wi-Fi 9. We then examine AI's role along three complementary dimensions, i.e., AI as a protocol (AI is applied to Wi-Fi's PHY/MAC operation), AI as a platform (Wi-Fi infrastructure is repurposed to provide AI computation), and AI as traffic (AI flows call for new traffic-handling policies), and discuss candidate features and open challenges along each. As a concrete illustration of the AI as traffic paradigm, we present a case study on AI traffic differentiation, where we explore a potential extension of the current Enhanced Distributed Channel Access (EDCA) to support new AI traffic flows.