Dynamic Modeling of Propagation Losses in 5G and Beyond Mobile Networks Using Real-Time Environmental Data
DOI:
https://doi.org/10.31838/NJAP/07.03.11Keywords:
5G, B5G, Propagation Loss, Real-Time Data, Dynamic Modelling, Environment-Aware Networks, Signal PredictionAbstract
Effective optimization of 5G and Beyond 5G (B5G) mobile networks relies on accurately predicting propagation losses, particularly at higher frequencies, which are more sensitive to environmental dynamic changes. Typical models used for propagation estimation rely on static parameters, which do not account for the existing variation in real-life rural, suburban, and urban environments. To address these gaps, this study proposes a novel dynamic modeling approach for estimating propagation losses with real-time environmental data, which includes weather, traffic, terrain changes, and urban development. The model utilizes IoT devices, remote sensing, and GIS to modify path loss calculations continuously, therefore improving adaptive resource allocation and contextual communication. The model outperforms static models in terms of prediction accuracy and network efficiency for dense urban areas. It accommodates the passive framework that pertains to the static prerequisites, such as ultra-low latency, ultra-low power consumption, ultra-high dependability, and resiliency, for future mobile networks. The advancement towards actively planned, optimized, and deployed responsive eco-adaptive mobile communication systems at the 5G and B5G levels is leveraged by this research.
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