Literature Database Entry

huenecke2025study

Jonas Hünecke, "Study on Channel State Information-based Distance Estimation using Off-the-Shelf Wi-Fi Hardware," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), September 2025. (Advisor: Sascha Rösler; Referees: Falko Dressler and Thomas Sikora)

Abstract

In the modern world, Internet-of-Things (IOT) devices are ubiquitous. A major role of devices is locating the device, with some devices, like AirTags build only for that exact purpose. Since Global Positioning System (GPS) suffers strong errors in indoor scenarios, many modern studies have looked into locating techniques based on Wi-Fi communication. To allow easy widespread implementation, such a system should be able to run using commodity and off-the-shelf hardware without special installation or firmware-patches. This thesis evaluates whether the tested hardware - Linux PCs with Intel AC9260 Network Interface Cards (NICs) and ESP32 microcontrollers - can deliver Channel State Information (CSI) records suitable for Time of Flight (TOF) estimation. To formalise testing parameters i have built a pipeline for CSI recording, error correction and TOF estimation and analysed the effect of different possible settings for CSI acquisition. Across both platforms, the reported CSI is strongly degraded but in different ways. While ESPs showed a strong non-linear trend, which may be caused by bad windowing/Cyclic Prefix (CP) removal in the ESPs internal Wi-Fi parts, Csiboxes reported very linear but extreme phase shifts across all subcarriers, which might be caused by a combination of Carrier Frequency Offset and Symbol Timing Offset. Correction techniques proposed in previous studies did not sufficiently correct these errors. As a result, neither estimator yielded a usable distance trend and errors remained on the order of many meters, with no consistent relation between phase slope and ground truth distance. This study concludes that CSI-based ranging is, although possible and promising in theory, ot reproducible on ESP32 and Intel AC9260 NICs and requires devices with accurate CSI estimation and reporting.

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Jonas Hünecke

BibTeX reference

@phdthesis{huenecke2025study,
    author = {H{\"{u}}necke, Jonas},
    title = {{Study on Channel State Information-based Distance Estimation using Off-the-Shelf Wi-Fi Hardware}},
    advisor = {R{\"{o}}sler, Sascha},
    institution = {School of Electrical Engineering and Computer Science (EECS)},
    location = {Berlin, Germany},
    month = {9},
    referee = {Dressler, Falko and Sikora, Thomas},
    school = {TU Berlin (TUB)},
    type = {Bachelor Thesis},
    year = {2025},
   }
   
   

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Last modified: 2026-04-20