Safe RAN control: A Symbolic Reinforcement Learning Approach

  title={Safe RAN control: A Symbolic Reinforcement Learning Approach},
  author={Alexandros Nikou and Anusha Mujumdar and Marin Orlic and Aneta Vulgarakis Feljan},
  journal={2022 IEEE 17th International Conference on Control \& Automation (ICCA)},
In this paper, we present a Symbolic Reinforcement Learning (SRL) based architecture for safety control of Radio Access Network (RAN) applications. In particular, we provide a purely automated procedure in which a user can specify high-level logical safety specifications for a given cellular network topology in order for the latter to execute optimal safe performance which is measured through certain Key Performance Indicators (KPIs). The network consists of a set of fixed Base Stations (BS… 

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