A simplified model for path loss estimation in Citrus Plantations at 3.5 GHz
Agriculture 4.0 represents a considerable increase in the number of sensors, as well as the appearance of new wireless technologies, which will meet the need to efficiently plan radio communication systems in agricultural environments. In this letter, a simplified model for path loss estimation in c...
| Autores: | , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad Politécnica de Cartagena(UPCT) |
| Repositorio: | Repositorio Digital UPCT |
| OAI Identifier: | oai:repositorio.upct.es:10317/13125 |
| Acceso en línea: | http://hdl.handle.net/10317/13125 https://ieeexplore.ieee.org/document/9739960 |
| Access Level: | acceso abierto |
| Palabra clave: | Precision agriculture Radio planning Radiowave propagation Teoría de la Señal y las Comunicaciones 3325.05 Radiocomunicaciones |
| Sumario: | Agriculture 4.0 represents a considerable increase in the number of sensors, as well as the appearance of new wireless technologies, which will meet the need to efficiently plan radio communication systems in agricultural environments. In this letter, a simplified model for path loss estimation in citrus plantations is proposed. The model assumes that, for long distances, the physical mechanism is a parallel transmission path over the treetops that can bemodeled by multiple-knife-edge diffraction. In our scenario, where the height of the transmitter is above the height of the trees, we proposed to estimate the multiple-knife-edge diffraction contribution by the settled field defined byWalfisch and Bertoni. In this way, the propagation losses estimated by the model have been compared with measurements carried out at 3.5 GHz in a lemon plantation before and after the fruit were collected. It has been observed that the slope of the regression line of the measurements yields values of 3.6 (with fruit) and 3.7 (without fruit), which are close to the value estimated by the model (3.8). The standard deviation of the prediction error given by the difference of the observed and estimated values is 4.5 dB (with fruit) and 3.2 dB (without fruit). |
|---|