Statistical Characterization and Modeling of Radio Frequency Signal Propagation in Mobile Broadband Cellular Next Generation Wireless Networks. (27th January 2023)

• Record Type: Journal Article
• Authors: Isabona, Joseph; Ibitome, Lanlege Louis; Imoize, Agbotiname Lucky; Mamodiya, Udit; Kumar, Ankit; Hassan, Montaser M.; Boakye, Isaac Kweku
• Other Names: Rajesh N. Academic Editor.
• Is Part Of: Computational intelligence and neuroscience. Volume 2023(2023)
• Publication Date: 2023-01-27
• Subjects: Neurosciences -- Data processing -- Periodicals; Computational intelligence -- Periodicals; Computational neuroscience -- Periodicals; 612.80285
• DOI: 10.1155/2023/5236566
• Languages: English
• ISSNs: 1687-5265

Abstract

Abstract : An accurate assessment of the spatial and temporal radio frequency channel characteristics is essential for complex signal processing and cellular network optimization. Current research has employed numerous models to figure out how much signal propagation loss occurs along the propagation paths. However, there are issues in finding the right model for a particular terrain because these models are not universally applicable. By employing the lognormal function and the Maximum Likelihood model, a hybrid probabilistic statistical distribution model was evolved. Three LTE cell site locations in Port Harcourt, Nigeria, were used to create a hybrid model that describes the functional stochastic signal propagation loss in the area. The evaluated Maximum Likelihood model accurately estimates the relevant wireless channel properties based on observed field data. The minor square regression approach and the proposed hybrid parameter estimation methodology are compared. When it comes to estimating standard deviation errors as well as the root mean square errors, the ML-based approach consistently outperforms the least square regression model. Finally, the proposed hybrid probabilistic statistical distribution model would be useful for mobile broadband network planning in related wireless propagation conditions.