ANN-based LoRaWAN channel propagation model

Habaebi, Mohamed Hadi and Mod Rofi, Ahmad Shahmi and Islam, Md. Rafiqul and Basahel, Ahmed (2022) ANN-based LoRaWAN channel propagation model. International Journal of Interactive Mobile Technologies, 16 (11). pp. 91-106. E-ISSN 1865-7923

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Abstract

LoRaWAN wireless communication channels are often impacted by noise and interference over long-range causing loss of a received signal. One of the main drawbacks of using existing propagation models is less accurate as these models in designing the communication link are tailored to simplify the estimation. In this paper, an artificial intelligent real time path loss model is proposed. It is capable of processing complex variables over a short period of time. Providing it with enough data, the model is able to learn channel behavior and predict the path loss accurately. Results of the model are benchmarked against classical statistical curve fitting models where RMSE values are also compared and indicating that the artificial intelligent model has better accurate prediction.

Item Type:	Article (Journal)
Uncontrolled Keywords:	artificial neural network, LoRAWAN channel, artificially intelligent, LoRa propagation loss models
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication. Including telegraphy, radio, radar, television
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User:	Dr. Mohamed Hadi Habaebi
Date Deposited:	11 Jun 2022 10:14
Last Modified:	11 Jun 2022 10:14
URI:	http://irep.iium.edu.my/id/eprint/98299

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