Poster: Comparison of Channel State Information driven and RSSI-based WiFi Distance Estimation

Publikation: KonferenzbeitragPosterBegutachtung


The ubiquity of WiFi and its wide adoption in consumer electronic devices is a major advantage of this technology with regard to radio-frequency based localization. For the distance estimation between devices, WiFi-based solutions either make use of the Received Signal Strength Indicator (RSSI) or of the Channel State Information (CSI). This work outlines the implementation of distance estimation approaches based on both RSSI and CSI measurements using the Nexmon CSI Extractor on Raspberry Pi 4 devices. Distances are estimated with the free-space attenuation model for RSSI data and with the FILA method for CSI data. We conducted preliminary experiments in the 2.4 GHz band, which show that distances calculated from CSI values have a smaller absolute median error than those calculated from RSSI values and therefore corroborate further research in this context. The gained results will serve as a benchmark for future WiFi-based distance estimation studies.
PublikationsstatusVeröffentlicht - Feb. 2021
Veranstaltung18th International Conference on Embedded Wireless Systems and Networks: EWSN 2021 - Virtuell, Delft, Niederlande
Dauer: 17 Feb. 202119 Feb. 2021


Konferenz18th International Conference on Embedded Wireless Systems and Networks
KurztitelEWSN '21
OrtVirtuell, Delft


  • WiFi
  • Localization
  • Distance Estimation
  • RSSI
  • Channel State Information

Fields of Expertise

  • Information, Communication & Computing

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