Elaris Computing Nexus
Design and Performance Evaluation of an AI-Driven Hybrid Simulation Model for LoRaWAN Networks
Elaris Computing Nexus
Received On : 06 September 2025
Revised On : 02 November 2025
Accepted On : 06 December 2025
Published On : 30 December 2025
Volume 01, 2025
Pages : 263-272
Abstract
This paper proposes an attempt to combine simulation and artificial intelligence (AI) to facilitate the operation of the LoRaWAN network. Our network parameters include transmit power, spreading factor, and coding rate, which we predict using deep learning (ANN, DNN, GRU), reinforcement learning (DQN, multi-agent RL), and ensemble strategies to find optimal parameters and maximize energy efficiency, packet success rate, and throughput. The approaches are tested through simulation with NS-3 and LoRaEnergySim platforms to validate them under realistic conditions of interference and traffic. Findings show that AI methods can substantially enhance resource allocation and conserve energy than the state-of-the-art methods, offering a solid framework of adaptive LoRaWAN network management.
Keywords
Artificial Neural Networks (ANNs), Energy Efficiency (EE), Network Optimization, Resource Allocation, NS-3 Simulator, Ensemble Learning, AI-Driven Networks, Industrial IoT (IIoT).
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CRediT Author Statement
The authors confirm contribution to the paper as follows:
Conceptualization: Arulmurugan Ramu; Methodology: Albin Hodza; Software: Arulmurugan Ramu; Data Curation: Arulmurugan Ramu; Writing- Original Draft Preparation: Albin Hodza and Arulmurugan Ramu; Visualization: Albin Hodza; Investigation: Arulmurugan Ramu; Supervision: Arulmurugan Ramu; Validation: Albin Hodza and Arulmurugan Ramu; Writing- Reviewing and Editing: Albin Hodza and Arulmurugan Ramu; All authors reviewed the results and approved the final version of the manuscript.
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Cite this Article
Arulmurugan Ramu and Albin Hodza, “Design and Performance Evaluation of an AI-Driven Hybrid Simulation Model for LoRaWAN Networks”, Elaris Computing Nexus, pp. 263-272, 2025, doi: 10.65148/ECN/2025024.
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© 2025 Arulmurugan Ramu and Albin Hodza. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.