On CSI and passive Wi-Fi radar for opportunistic physical activity recognition

Wenda Li, Mohammud Junaid Bocus, Chong Tang, Robert J. Piechocki, Karl Woodbridge, Kevin Chetty

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)
77 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)607-620
Number of pages14
JournalIEEE Transactions on Wireless Communications
Volume21
Issue number1
DOIs
Publication statusPublished - 27 Jul 2021

Keywords

  • Passive Wi-Fi radar
  • channel state information
  • Doppler
  • wireless sensing
  • Hidden Markov models
  • Wireless communication
  • OFDM
  • Sensors
  • Wireless fidelity
  • Wireless sensor networks

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