On CSI and Passive Wi-Fi Radar for Opportunistic Physical Activity Recognition

• Published in: IEEE transactions on wireless communications Vol. 21; no. 1; pp. 607 - 620
• Main Authors: Li, Wenda, Bocus, Mohammud Junaid, Tang, Chong, Piechocki, Robert J., Woodbridge, Karl, Chetty, Kevin
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-01-2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Activity recognition; channel state information; Doppler; Exercise; Hidden Markov models; Human activity recognition; Human influences; Human motion; Human performance; Line of sight; Multistatic radar; OFDM; Passive Wi-Fi radar; Sensors; Signal processing; Wireless communication; Wireless fidelity; wireless sensing; Wireless sensor networks
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2021.3098526

The use of Wi-Fi signals for human sensing has gained significant interest over the past decade. Such techniques provide affordable and reliable solutions for healthcare-focused events such as vital sign detection, prevention of falls and long-term monitoring of chronic diseases, among others. Currently, there are two major approaches for Wi-Fi sensing: (1) passive Wi-Fi radar (PWR) which uses well established techniques from bistatic radar, and channel state information (CSI) based wireless sensing (SENS) which exploits human-induced variations in the communication channel between a pair of transmitter and receiver. However, there has not been a comprehensive study to understand and compare the differences in terms of effectiveness and limitations in real-world deployment. In this paper, we present the fundamentals of the two systems with associated methodologies and signal processing. A thorough measurement campaign was carried out to evaluate the human activity detection performance of both systems. Experimental results show that SENS system provides better detection performance in a line-of-sight (LoS) condition, whereas PWR system performs better in a non-LoS (NLoS) setting. Furthermore, based on our findings, we recommend that future Wi-Fi sensing applications should leverage the advantages from both PWR and SENS systems.