Novel Soil Impact Prediction Model on Bandwidth Mounir El Mejjatti, Ahmed Habbani Proceedings 10th International Conference on Wireless Networks and Mobile Communications Wincom 2023, 2023
Regression analysis-based identification model of key impactful parameters on buried antennas Mounir El Mejjatti, Ahmed Habbani, Faissal El Bouanani International Journal of Communication Systems, 2022 SummaryThe antenna's bandwidth is strongly dependent on its physical properties and the environment where it is located. Nevertheless, for transmitting devices embedded permanently in the soil, the propagation medium's properties are unstable due to dielectric permittivity's spatial and temporal changes. Relying on soil parameters values, we present three new multivariable regression models allowing a good fit to the dataset curves with antenna's resonant frequency variations prediction of about 98%. Precisely, such models have been obtained with the help of the multiple linear regression analysis method. Additionally, the results revealed that amongst four considered parameters (i.e., volumetric moisture, bulk density, specific density, and temperature), volumetric moisture is the most influencing factor on the antenna operating frequency band with a correlation coefficient of −0.989, whereas it equals 0.04, −0.035, and −0.002 for the temperature, bulk density, and specific density, respectively.
