Unleashing the potential of machine learning to address spatial reuse in future IEEE 802.11 WLANs: an introduction to two problem statements for the ITU AI Challenge

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Unleashing the potential of machine learning to address spatial reuse in future IEEE 802.11 WLANs: an introduction to two problem statements for the ITU AI Challenge

Spatial Reuse (SR) is one of the techniques that is gaining more attention in next-generation IEEE 802.11 standards. SR was firstly introduced in the IEEE 802.11ax (11ax) as a decentralized mechanism, but it is now evolving with IEEE 802.11be (11be) thanks to the multi Access Point (multi-AP) feature. In both cases, SR aims at increasing the number of parallel transmissions in an Overlapping Basic Service Set (OBSS) by applying sensitivity adjustment and transmit power control. In this talk, we will provide an overview of both 11ax and 11be SR mechanisms and discuss two problem statements for the ITU AI Challenge, where participants must harness the potential of Machine Learning (ML) to solve a relevant problem in communications such as the SR one.

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