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Title
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A primer on real-world RSS-based outdoor NB-IoT localization
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Author
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Abstract
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| Apart from long range communication, Low Power Wide Area Networks (LPWAN) are used to locate Internet of Things (IoT) devices. With hundreds of networks being deployed in a short amount of time, NarrowBand IoT (NB-IoT) is stealing the LPWAN market shares from its competitors. The deep indoor coverage of NB-IoT guarantees the energy-efficient communication link between a device and a nearby base station. We believe we are the first to perform signal strength-based outdoor localization experiments with this up-and-coming technology. Instead of simulating the experiments, we face the challenges of working with real measurements in a real-world city-scale environment. In contrast to satellite-based solutions, the position of a mobile device equipped with a small battery can be estimated in indoor and outdoor environments for several years. In this research, we investigate the accuracy of NB-IoT localization, using the Received Signal Strength (RSS) to a single NB-IoT base station antenna. We evaluate three outdoor RSS-based algorithms: proximity, ranging and optimized fingerprinting. The experiments result in a mean location estimation error of 340 m, 320 m and 204 m, respectively. |
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Language
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English
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Source (journal)
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International Conference on Localization and GNSS : [proceedings]. - Piscataway, NJ
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Source (book)
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2020 International Conference on Localization and GNSS (ICL-GNSS), 2-4 June, 2020, Tampere, Finland
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Publication
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Piscataway, NJ
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IEEE
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2020
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ISSN
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2325-0747
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ISBN
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978-1-7281-6455-7
978-1-7281-6456-4
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DOI
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10.1109/ICL-GNSS49876.2020.9115578
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Volume/pages
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p. 1-6
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ISI
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000695708800028
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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