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Measuring a LoRa Network: Performance, Possibilities and Limitations

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Internet of Things, Smart Spaces, and Next Generation Networks and Systems (NEW2AN 2018, ruSMART 2018)

Abstract

Low power wide area (LPWA) technologies becomes popular for IoT use cases because LPWA is enable the broad range communications and allows to transmit small amounts of information in a long distance. Among LPWA technologies there are LTE-M, SigFox, LoRa, Symphony Link, Ingenu RPMA, Weightless, and NB-IoT. Currently all these technologies suffer from lack of documentation about deployment recommendation, have non-investigated limitations that can affect implementations and products using such technologies. This paper is focused on the testing of LPWAN LoRa technology to learn how a LoRa network gets affected by different environmental attributes such as distance, height and surrounding area by measuring the signal strength, signal to noise ratio and any resulting packet loss. The series of experiments for various use cases are conducted using a fully deployed LoRa network made up of a gateway and sensor available through the public network. The results will show the LoRa network limitation for such use cases as forest, city, open space. These results allow to give the recommendation for companies during early analysis and design stages of network life circle, and help to choose properly technology for deployment an IoT application.

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Correspondence to Ievgeniia Kuzminykh .

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Carlsson, A., Kuzminykh, I., Franksson, R., Liljegren, A. (2018). Measuring a LoRa Network: Performance, Possibilities and Limitations. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2018 2018. Lecture Notes in Computer Science(), vol 11118. Springer, Cham. https://doi.org/10.1007/978-3-030-01168-0_11

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  • DOI: https://doi.org/10.1007/978-3-030-01168-0_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01167-3

  • Online ISBN: 978-3-030-01168-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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