Machine learning for joint sensing and communication in future millimeter wave IEEE 802.11 WLANs

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Machine learning for joint sensing and communication in future millimeter wave IEEE 802.11 WLANs

Millimeter wave spectrum offers not only large bandwidth for high throughput communication but also great opportunities for sensing applications.

With the ubiquity of WiFi devices in our life, re-using these devices and the previous protocols become a unique opportunity to enable new applications such as presence detection, gesture recognition, or person identification.  In this context, IEEE has recently started a new task group, TGbf, to enhance the reliability and efficiency of WLAN sensing, introducing IEEE 802.11bf, which extends the current IEEE 802.11ay functionalities.

This talk will provide an overview of IEEE 802.11ay/bf, presenting the ITU AI/ML Challenge and the datasets provided. In the challenge participants are invited to apply ML techniques to shed light on the sensing and localization performance in indoor environments.

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