Literature Database Entry


Anatolij Zubow, Christos Laskos and Falko Dressler, "Toward the Simulation of WiFi Fine Time Measurements in NS3 Network Simulator," Elsevier Computer Communications, vol. 210, pp. 35–44, October 2023.


WiFi has become the most widely used indoor positioning technology. The Fine Time Measurement (FTM) protocol introduced in the IEEE 802.11-2016 standard uses radio frequency based two-way time-of-flight (ToF) estimation, which promises precise indoor ranging and positioning. However, even with an ToF approach an exact indoor positioning is challenging due to the peculiarities of the propagation of the wireless signal such as signal attenuation, multipath propagation and signal fading. Moreover, the used WiFi hardware and its configuration like channel bandwidth also plays a major role. We present FTM-ns3, a software module which implements the 802.11 FTM protocol so that it can be used within the widely used ns3 network simulator. Moreover, we conducted experiments using commodity WiFi-FTM hardware, Intel 8260 and ESP32, and derived empirical error models which can be used in simulations to study the performance of novel FTM-based localization schemes under real channel propagation conditions while taking into account the specifics of the used WiFi hardware and configuration of FTM. Finally, we present results from simulations of a simple localization scheme based on FTM and multilateration which show the great influence of ranging inaccuracy introduced due to multipath propagation in typical indoor environments with line-of-sight (LoS) but strong multipath. Our module is provided to the community as open source and can be easily customized and extended.

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Anatolij Zubow
Christos Laskos
Falko Dressler

BibTeX reference

    author = {Zubow, Anatolij and Laskos, Christos and Dressler, Falko},
    doi = {10.1016/j.comcom.2023.07.028},
    title = {{Toward the Simulation of WiFi Fine Time Measurements in NS3 Network Simulator}},
    pages = {35--44},
    journal = {Elsevier Computer Communications},
    issn = {0140-3664},
    publisher = {Elsevier},
    month = {10},
    volume = {210},
    year = {2023},

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