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Title
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RSS-based localization and mobility evaluation using a single NB-IoT cell
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Author
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Abstract
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| Low Power Wide Area Networks (LPWAN) have the ability to localize a mobile transmitter using signals of opportunity, as a low power and low cost alternative to satellite-based solutions. In this paper, we evaluate the accuracy of three localization approaches based on the Received Signal Strength (RSS). More specifically, the performance of a proximity, range-based and optimized fingerprint-based algorithm is evaluated in a large-scale urban environment using a public Narrowband Internet of Things (NB-IoT) network. The results show a mean location estimation error of 340, 320 and 204 m, respectively. During the measurement campaign, we discovered a mobility issue in NB-IoT. In contrast to other LPWAN and cellular technologies which use multiple gateways or cells to locate a device, only a single cell antenna can be used for RSS-based localization in NB-IoT. Therefore, we address this limitation in the current NB-IoT hardware and software by studying the mobility of the cellular-based 3GPP standard in a localization context. Experimental results show that the lack of handover support leads to increased cell reselection time and poor cell sector reliability, which in turn results in reduced localization performance. |
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Language
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English
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Source (journal)
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Sensors. - -
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Publication
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2020
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ISSN
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1424-8220
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DOI
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10.3390/S20216172
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Volume/pages
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20
:21
(2020)
, 14 p.
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Article Reference
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6172
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ISI
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000589314700001
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Pubmed ID
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33138281
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Medium
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E-only publicatie
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Full text (Publisher's DOI)
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Full text (open access)
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