Literature Database Entry

petto2023presence

Kim Felix Petto, "Presence Detection using Channel State Information from 802.11 WiFi," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), May 2023. (Advisor: Anatolij Zubow; Referees: Falko Dressler and Thomas Sikora)

Abstract

We study the use of Channel State Information (CSI) to perform device-free in- door presence detection. Many devices using WiFi implement the IEEE 802.11n/ac standard. Using Orthogonal Frequency-Division Multiplexing (Orthogonales Frequenzmultiplexverfahren, OFDM) and Multiple-Input, Multiple-Output (MIMO) allows receiving devices to measure CSI. It contains rich information about the propagated environment of Radio Frequency (RF) signals and is used extensively in device-free sensing applications. To perform binary presence detection, CSI has to be gathered from an environment with and without presence. Gathering data with presence can be difficult, as the whole data needs to ideally resemble the person in all possible locations within the environment. Furthermore, in indoor environments there are possibly multiple existing devices operating on the finite frequency spectrum of WiFi which could lead to interference. To face these challenges, we use an existing approach of pre- and postprocessing and propose a presence detection system that considers human presence as a novelty. In experiments we train this system using CSI gathered from empty rooms and test it with CSI gathered from both, empty and occupied rooms. Our results show that our system is robust when reducing the channel width and transmission rate up to a threshold. It is more sensitive to a drastically reduced transmission rate than a drastically reduced channel width. We conclude that Wi-Fi devices performing presence detection can use lower bandwidths in their signals, allowing more users operating concurrently on its finite frequency band.

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Kim Felix Petto

BibTeX reference

@phdthesis{petto2023presence,
    author = {Petto, Kim Felix},
    title = {{Presence Detection using Channel State Information from 802.11 WiFi}},
    advisor = {Zubow, Anatolij},
    institution = {School of Electrical Engineering and Computer Science (EECS)},
    location = {Berlin, Germany},
    month = {5},
    referee = {Dressler, Falko and Sikora, Thomas},
    school = {TU Berlin (TUB)},
    type = {Bachelor Thesis},
    year = {2023},
   }
   
   

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Last modified: 2024-05-04