The Machine Learning based Propagation Loss (MLPL) model is a module for the network simulator 3 (ns-3) that uses machine learning to train a propagation loss model to reproduce the physical conditions of an experimental testbed. The propagation loss model is trained with network traces collected in the experimental testbed that shall be reproduced.
Copyright (C) 2020-2023, INESC TEC. This project is licensed under the terms of the European Union Public Licence (EUPL) v1.2
This project is authored by:
All stable releases of the MLPL module are available in the GitLab Releases page.
The MLPL module contains two models depending on the method to train and predict the propagation loss.
They are both implemented in the same set of files. The term MLPL is used to refer the generic model, regardless of the specific sub-model used. The specific sub-models are referred by their acronyms.
The list of publications in international conferences and journals about the MLPL model is available in the following page:
If you would like to use this module, please cite it as follows:
Eduardo Nuno Almeida, Helder Fontes, Rui Campos, and Manuel Ricardo. 2023. Position-Based Machine Learning Propagation Loss Model Enabling Fast Digital Twins of Wireless Networks in ns-3. In Proceedings of the 2023 Workshop on ns-3 (WNS3 '23). ACM, 69β77. https://doi.org/10.1145/3592149.3592150
π Presentation Slides ποΈ Presentation Video
π Best Paper Award π ACM Artifacts Available Badge
Works with ns-3.41
Build History : ML Propagation Loss Model 1.0.2Release Notes
Release date: 13 May 2024
Works with ns-3.41
Build History : ML Propagation Loss Model 1.0.1Release Notes
Release date: 16 November 2023
Works with ns-3.40
Build History : ML Propagation Loss Model 1.0Release Notes
Release date: 19 October 2023
The MLPL module depends on other ns-3 App Store modules. The list of dependencies and their installation instructions are explained in the MLPL's README.
The instructions to download and setup the MLPL module are described in the MLPL's README.
Bug reports or feature suggestions can be made by creating an issue in the issue tracker.
Contributions to this module are welcome. If you would like to contribute to this module, feel free to open a merge request.
Contributions to this module are subject to the license terms defined in this repository.
This module is open-source and developed in the MLPL GitLab repository.
The official releases of the MLPL module are stored in the MLPL GitLab Releases page.
This ns-3 extension is one or more contributed modules.