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Thanks to the ubiquitous deployment of Wi-Fi hotspots, channel stateinformation (CSI)-based Wi-Fi sensing can unleash game-changing applications inmany fields, such as healthcare, security, and entertainment. However, despiteone decade of active research on Wi-Fi sensing, most existing work onlyconsiders legacy IEEE 802.11n devices, often in particular andstrictly-controlled environments. Worse yet, there is a fundamental lack ofunderstanding of the impact on CSI-based sensing of modern Wi-Fi features, suchas 160-MHz bandwidth, multiple-input multiple-output (MIMO) transmissions, andincreased spectral resolution in IEEE 802.11ax (Wi-Fi 6). This work aims toshed light on the impact of Wi-Fi 6 features on the sensing performance and tocreate a benchmark for future research on Wi-Fi sensing. To this end, weperform an extensive CSI data collection campaign involving 3 individuals, 3environments, and 12 activities, using Wi-Fi 6 signals. An anonymized groundtruth obtained through video recording accompanies our 80-GB dataset, whichcontains almost two hours of CSI data from three collectors. We leverage ourdataset to dissect the performance of a state-of-the-art sensing frameworkacross different environments and individuals. Our key findings suggest that(i) MIMO transmissions and higher spectral resolution might be more beneficialthan larger bandwidth for sensing applications; (ii) there is a pressing needto standardize research on Wi-Fi sensing because the path towards a trulyenvironment-independent framework is still uncertain. To ease the experiments'replicability and address the current lack of Wi-Fi 6 CSI datasets, we releaseour 80-GB dataset to the community.

Exposing the CSI: A Systematic Investigation of CSI-based Wi-Fi Sensing Capabilities and Limitations