Reinforcement Learning to Minimize Age of Information with an Energy Harvesting Sensor with HARQ and Sensing Cost

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Ceran E. T. , Gunduz D., Gyorgy A.

IEEE Conference on Computer Communications (IEEE INFOCOM), Paris, France, 29 April - 02 May 2019, pp.656-661 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/infcomw.2019.8845182
  • City: Paris
  • Country: France
  • Page Numbers: pp.656-661


The time average expected age of information (AoI) is studied for status updates sent from an energy-harvesting transmitter with a finite-capacity battery. The optimal scheduling policy is first studied under different feedback mechanisms when the channel and energy harvesting statistics are known. For the case of unknown environments, an average-cost reinforcement learning algorithm is proposed that learns the system parameters and the status update policy in real time. The effectiveness of the proposed methods is verified through numerical results.