2021
DOI: 10.3390/s21082717
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Cityscape LoRa Signal Propagation Predicted and Tested Using Real-World Building-Data Based O-FDTD Simulations and Experimental Characterization

Abstract: The age of the Internet of Things (IoT) and smart cities calls for low-power wireless communication networks, for which the Long-Range (LoRa) is a rising star. Efficient network engineering requires the accurate prediction of the Received Signal Strength Indicator (RSSI) spatial distribution. However, the most commonly used models either lack the physical accurateness, resolution, or versatility for cityscape real-world building distribution-based RSSI predictions. For this purpose, we apply the 2D electric fi… Show more

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Cited by 4 publications
(2 citation statements)
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“…This equation is made by measuring the signal strength at a certain distance from the gateway performance. Linear regression VOLUME 11, 2023 models the relationship between variables affecting RSSI, gateways, building distribution, SNR, and distance to increase the number of gateways or rearrange the frequency of data transmission [25], [34].…”
Section: E Linear Regressionmentioning
confidence: 99%
“…This equation is made by measuring the signal strength at a certain distance from the gateway performance. Linear regression VOLUME 11, 2023 models the relationship between variables affecting RSSI, gateways, building distribution, SNR, and distance to increase the number of gateways or rearrange the frequency of data transmission [25], [34].…”
Section: E Linear Regressionmentioning
confidence: 99%
“…The simulation results show the received signal estimation for an area of 100 × 200 m 2 . Dão et al [ 63 ] predicted the received signal using the Oscillator Finite-Difference Time-Domain (O-FDTD) method. The authors state that this model may become unsustainable for LoRa maps much larger than 600 × 600 m 2 .…”
Section: Introductionmentioning
confidence: 99%