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

Creative Commons License

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

IEEE Conference on Computer Communications (IEEE INFOCOM), Paris, Fransa, 29 Nisan - 02 Mayıs 2019, ss.656-661 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/infcomw.2019.8845182
  • Basıldığı Şehir: Paris
  • Basıldığı Ülke: Fransa
  • Sayfa Sayıları: ss.656-661
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

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.