ANN-based LoRaWAN Channel Propagation Model

Authors

  • Mohamed Hadi Habaebi International Islamc University Malaysia (IIUM), Kuala Lumpur, Malaysia
  • Ahmad Shahmi Mod Rofi International Islamc University Malaysia (IIUM), Kuala Lumpur, Malaysia
  • Md Rafiqul Islam International Islamc University Malaysia (IIUM), Kuala Lumpur, Malaysia
  • Ahmed Basahel First Fuel Company, Jedah, Saudi Arabia

DOI:

https://doi.org/10.3991/ijim.v16i11.30095

Keywords:

Artificial neural network, LoRAWAN channel, artificially intelligent, LoRa propagation loss models

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.

Cover iJIM Vol. 16 No. 11 (2022)

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Published

2022-06-07

How to Cite

Mohamed Hadi Habaebi, Ahmad Shahmi Mod Rofi, Md Rafiqul Islam, & Ahmed Basahel. (2022). ANN-based LoRaWAN Channel Propagation Model . International Journal of Interactive Mobile Technologies (iJIM), 16(11), pp. 91–106. https://doi.org/10.3991/ijim.v16i11.30095

Issue

Vol. 16 No. 11 (2022)

Section

Papers

License

Copyright (c) 2022 Mohamed Hadi Habaebi, Ahmad Shahmi Mod Rofi, Md Rafiqul Islam, Ahmed Basahel

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