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BeamSense: MU-MIMO Beamforming Feedback Dataset for Wi-Fi Sensing
Dataset Summary
BeamSense is a large-scale MU-MIMO Wi-Fi sensing dataset built upon Beamforming Feedback Information (BFI) and Channel State Information (CSI) collected from commodity 802.11ac devices. The dataset corresponds to the research presented in:
BeamSense: Rethinking Wireless Sensing with MU-MIMO Wi-Fi Beamforming Feedback (Computer Networks, 2025)
BFA-Sense: Learning Beamforming Feedback Angles for Wi-Fi Sensing (PerCom Workshops, 2024)
BeamSense contains synchronized BFI, BF angles, and CSI samples from multiple Wi-Fi stations (STAs) under different environments and orientations. It is designed for:
- Human activity recognition with Beamforming Feedback Information (BFI) and CSI
- Gesture recognition with Beamforming Feedback Information (BFI) and CSI
- Device-free sensing with BFI
- Cross-domain generalization
- Beamforming Feedback analysis
- Beamforming Feedback-based attacks
- Wi-Fi sensing algorithm development
Dataset Contents
- Raw Beamforming Feedback Packet Captures: Contains BF report packets (BFI), and PHY metadata
- Synchronized CSI: Extracted from PCAPs using Nexmon-modified pipelines
- Synchronized BFI and CSI
Multi-Environment, Multi-Day Collection:
- Includes data from: Office, Classroom, and Kitchen environments
- LOS and NLOS cases
- Multiple days of data collection
- 3 Different human subjects perform 20 different activities in multiple environments and orientations
- Spatially diverse data from multiple STAs
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