ATHENA: Machine Learning and Reasoning for Radio Resources Scheduling in vRAN systems

The repository contains the code of the paper "ATHENA: Machine Learning and Reasoning for Radio Resources Scheduling in vRAN systems" by N. Apostolakis, M. Gramaglia, L.E. Chatzieleftheriou, T. Subramanya, A. Banchs, H. Sanneck in IEEE Journal on Selected Areas in Communications, doi: 10.1109/JSAC.2023.3336155.

Please cite the paper if you plan to use it in your publication.

@ARTICLE{10329922,
  author={Apostolakis, Nikolaos and Gramaglia, Marco and Chatzieleftheriou, Livia Elena and Subramanya, Tejas and Banchs, Albert and Sanneck, Henning},
  journal={IEEE Journal on Selected Areas in Communications}, 
  title={ATHENA: Machine Learning and Reasoning for Radio Resources Scheduling in vRAN Systems}, 
  year={2024},
  volume={42},
  number={2},
  pages={263-279},
  keywords={Cognition;Biological system modeling;3GPP;Throughput;Computer architecture;Automation;Radio access networks;vRAN;radio resource scheduling;deep reinforcement learning;machine reasoning},
  doi={10.1109/JSAC.2023.3336155}}

To get started, clone this repository to your local machine using the following command:

git clone --recurse-submodules [email protected]:/kaposnick/athena_agent.git

and navigate to the project repository:

cd athena_agent

Instructions on setting up the server and running scenarios can be found in the scenarios/ folder. Please refer to the respective markdown files for detailed guidance.

If you encounter any issues or have questions, feel free to open an issue or reach out to us.