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An Artificial Intelligence Approach to Ultra-High Frequency Path Loss Modelling of the Suburban Areas of Abuja, Nigeria

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An Artificial Intelligence Approach to Ultra-High Frequency Path Loss Modelling of the Suburban Areas of Abuja, Nigeria


Deme C. Abraham



Deme C. Abraham "An Artificial Intelligence Approach to Ultra-High Frequency Path Loss Modelling of the Suburban Areas of Abuja, Nigeria" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2, February 2020, pp.1114-1118, URL: https://www.ijtsrd.com/papers/ijtsrd30227.pdf

This study proposes Artificial Intelligence (AI) based path loss prediction models for the suburban areas of Abuja, Nigeria. The AI-based models were created on the bases of two deep-learning networks, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Generalized Radial Basis Function Neural network (RBF-NN). These prediction models were created, trained, validated and tested for path loss prediction using path loss data recorded at 1800MHz from multiple Base Transceiver Stations (BTSs) distributed across the areas under investigation. Results indicate that the ANFIS and RBF-NN based models with Root Mean Squared Error (RMSE) values of 5.30dB and 5.31dB respectively, offer greater prediction accuracy over the widely used empirical COST 231 Hata, which has an RMSE of 8.18dB.

Path Loss; Adaptive Neuro-Fuzzy Inference System; Generalized Radial Basis Function Neural Network; Multi-Layer Perceptron Neural Network; Hata-Okumura


IJTSRD30227
Volume-4 | Issue-2, February 2020
1114-1118
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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