Tools, Models and Dataset for IEEE 802.11ay CSI-based Sensing

The ubiquitous deployment and availability of wireless communications devices, coupled with recent technical advancements, provide a unique opportunity to enable wireless sensing applications, leveraging existing communications equipment and signals. The availability of modeling tools and dataset is crucial to support the development of sensing techniques and to understand the end-to-end performance of a joint wireless communication and sensing system. However, most of the sensing performance evaluations are carried out using proprietary tools and dataset. In this paper, we present a set of open source tools and models enabling the evaluation of future WLAN sensing systems. Our framework is composed of a ray-tracing implementation specific for sensing application, an IEEE 802.11ay physical layer (PHY) digital transceiver model and a visualization application. Using these tools, we design a dataset consisting of more than 14 000 entries of millimeter wave channels and IEEE 802.11 ay signals to democratize the design of both data-driven and model driven communication and sensing algorithms. We also provide a preliminary evaluation of a CSI-based WLAN sensing system using IEEE 802.11 ay signals. The results indicate that existing communication systems can be used to enable sensing applications.