![]() This paper reviews the performance of LP-WAN technologies for IoT, including design choices and their implications. However, this has also created another challenge pertaining to technology selection. The rapid growth of Internet-of-Things (IoT) in the current decade has led to the development of a multitude of new access technologies targeted at low power, wide area networks (LP-WANs). To stimulate further research in this direction, we make all our data publicly available. In addition, we derive estimations for the needed sample size in similar measurement campaigns. Our results reveal that the Log-distance model and other well-known empirical models such as Okumura or Winner+ provide reasonable estimations in an urban environment, and terrain based models such as ITM or ITWOM have no advantages. Using this data, we compare eleven previously proposed path loss models and additionally provide new coefficients for the Log-distance model. In this paper, we report on a corresponding large-scale measurement study covering an urban area of 200km2 over a period of 230 days using sensors deployed on garbage trucks, resulting in more than 112 thousand high-quality samples for received packet power. Path loss models aid in this task, but evaluating and comparing different models requires a sufficiently large set of high-quality received packet power samples. One core challenge in rolling out and operating these networks is radio network planning, i.e., precise predictions about possible new locations and their impact on network coverage. Urban LoRa networks promise to provide a cost-efficient and scalable communication backbone for smart cities. ![]()
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December 2022
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