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ZENODO
Dataset . 2018
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2018
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2018
License: CC BY
Data sources: ZENODO
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LoRaWAN Measurement Campaigns in Lebanon

Authors: Rida El Chall; Samer Lahoud; Melhem El Helou;

LoRaWAN Measurement Campaigns in Lebanon

Abstract

LoRaWAN is a promising technology for the internet of things (IoT) in order to support low power and long-range communications. However, real-world deployment and network optimization require an accurate path-loss modeling in order to estimate network coverage and performance. We carried out extensive measurement campaigns in both indoor and outdoor environments considering urban and rural areas in three locations in Lebanon (Saint Joseph University campus, Beirut city, and Bekaa valley). We further consider 3 different antennas heights of the end-device (0.2m-3m). This dataset provides these measurements campaigns, which enable us to derive Path-loss (PL) models for Lora communication. A text file “Readme_data” is provided to describe the measurements in addition a Matlab function of the proposed model “Path-Loss-Model” is given.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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