Analysis of Lora Signal Propagation in Urban Environment

This paper analyzes LoRa signal propagation in an urban environment, based on RSSI collections conducted at various distances ranging from 10 to 1610 meters. The data were analyzed using the log-normal shadowing model, allowing the generation of path loss graphs. The coefficient of determination (R²) for the log-normal model was 0.9764, with an RMSE of 3.2872 and an MAE of 2.4020, indicating an excellent fit to the data. As a comparison between regression methods, the quadratic approximation presented an R² of 0.9117, RMSE of 6.1397, and MAE of 5.2137, reflecting lower performance. These results highlight the impact of distance on signal attenuation and confirm the effectiveness of the log-normal shadowing model in representing propagation in urban scenarios. The research contributes to understanding LoRa performance in dense environments, providing valuable insights for the planning and optimization of LoRa networks, as well as serving as a practical guide for future applications in the Internet of Things context.

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Publication Details

Journal
ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA)
Published
2025-01-01
DOI
https://doi.org/10.5935/jetia.v11i53.1571
Primary Topic
Radio Wave Propagation Studies
Type
article
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article

Analysis of Lora Signal Propagation in Urban Environment

David Ferreira
ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA)
Radio Wave Propagation Studies
article

Analysis of Lora Signal Propagation in Urban Environment

David Ferreira
article en

Abstract

This paper analyzes LoRa signal propagation in an urban environment, based on RSSI collections conducted at various distances ranging from 10 to 1610 meters. The data were analyzed using the log-normal shadowing model, allowing the generation of path loss graphs. The coefficient of determination (R²) for the log-normal model was 0.9764, with an RMSE of 3.2872 and an MAE of 2.4020, indicating an excellent fit to the data. As a comparison between regression methods, the quadratic approximation presented an R² of 0.9117, RMSE of 6.1397, and MAE of 5.2137, reflecting lower performance. These results highlight the impact of distance on signal attenuation and confirm the effectiveness of the log-normal shadowing model in representing propagation in urban scenarios. The research contributes to understanding LoRa performance in dense environments, providing valuable insights for the planning and optimization of LoRa networks, as well as serving as a practical guide for future applications in the Internet of Things context.

ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA)Vol. 11(53)
Sustainable cities and communities
Openalex Percentile: Top 84%
Radio Wave Propagation Studies
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