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Author: search.filters.author.Supanakoon, PichayaSubject: search.filters.subject.Bluetooth low energy (BLE) beacon

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    Evaluation of distance error with bluetooth low energy transmission model for indoor positioning
    (2021-06-02)
    Supanakoon, Pichaya
    ;
    Promwong, Sathaporn
    Currently, an indoor positioning is a challenge application for location-based services (LBS) and proximity-based services (PBS). However, the indoor channel has dense multipath fading, causing more distance error than outdoor positioning. In this paper, the distance error analysis model is proposed for indoor positioning. The indoor channel is modeled as the sum of path loss model and multipath fading model. The path loss model is a linear regression model (LRM) based on Friis' transmission formula, used for estimating the distance from received signal strength (RSS). The multipath fading is a Gaussian statistical model with zero mean, used for characterizing the multipath fading effect. The normalized distance error is evaluated and defined. The indoor channel with Bluetooth low energy (BLE) beacons is measured and compared with the proposed model. From the results, the normalized distance error obtained from the proposed model corresponds very well to measurement. This proposed model can be used as a tool for designing an indoor positioning system to obtain the specific distance error.
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    Accuracy Study of Indoor Positioning with Bluetooth Low Energy Beacons
    (2020-03-01)
    Phutcharoen, Kanyanee
    ;
    Chamchoy, Monchai
    ;
    Supanakoon, Pichaya
    Currently, Bluetooth low energy (BLE) beacons are widely used for positioning, especially an indoor environment. However, there is still high error due to dense multipath fading that often occurs in the indoor environment. This paper presents the accuracy study of indoor positioning with BLE beacons. The indoor environment is the room of 91.8 m<sup>2</sup> with 3 BLE beacons. The user equipment (UE), iPhone XS Max, with Beacon Analyzer application is used to measure the received signal strength (RSS) of each BLE beacon. Fingerprinting technique with least root mean square (RMS) error matching is used to estimate the position of UE. The accuracy that obtained from single measurement and average five measurements is studied. The RSS fingerprint of each BLE beacon is shown. The cumulative distribution function (CDF) of distance error is evaluated and illustrated. From the results, the average five measurements can reduce the average distance error about 0.86 m.