NikolaiMadlener / link-quality-estimation

Code samples and datasets that are related to link quality estimation.

Link quality estimation

Code samples and datasets that are related to link quality estimation.

Directory structure

datasets

Datasets (and their corresponding Python scripts) that are related to link quality estimation.

notebooks

Jupyter notebooks that are related to the datasets analysis and/or link quality estimation.

Conventional work flow

1. Install python dependencies
2. Run desired scripts directly (e.g. python ./datasets/trace1_Rutgers/transform.py)
3. Perform analysis on preprocessed dataset:
   • Use your own tools on CSV files, which were produced in ./output/datasets/<dataset_name>/
   • or use this project as python package and adapt it to your needs. (e.g. from datasets.trace1_Rutgers import get_traces)

Citation

If you are using our datasets or scripts in your research, citation of any of the following papers would be greatly appreciated.

Cerar, G., Yetgin, H., Mohorčič, M., Fortuna, C. (2021). Machine Learning for Link Quality Estimation: A Survey

Kulin, M., Fortuna, C., De Poorter, E., Deschrijver, D., & Moerman, I. (2016). Data-Driven Design of Intelligent Wireless Networks: An Overview and Tutorial. Sensors, 16(6), 790.

Work in progress

This repository is gradually migrating toward Python 3.4+ and package oriented approach. Trace1_Rutgers is currently up to date, while unfortunately other datasets may require Python 2 with obsolete packages for preprocessing. We are sorry for inconvenience.

License

See README.md files in individual sub-directories for details.

Acknowledgement

The research leading to these results has received funding from the European Horizon 2020 Programme projects NRG-5 under grant agreement No. 762013 and eWINE under grant agreement No. 688116.