Learning to Minimize Age of Information over an Unreliable Channel with Energy Harvesting
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Abstract (arXiv)
The time average expected age of information (AoI) is studied for status updates sent over an error-prone channel from an energy-harvesting transmitter with a finite-capacity battery. Energy cost of sensing new status updates is taken into account as well as the transmission energy cost better capturing practical systems. The optimal scheduling policy is first studied under the hybrid automatic repeat request (HARQ) protocol when the channel and energy harvesting statistics are known, and the existence of a threshold-based optimal policy is shown. For the case of unknown environments, average-cost reinforcement-learning algorithms are proposed that learn the system parameters and the status update policy in real-time. The effectiveness of the proposed methods is demonstrated through numerical results.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 43 references that are in the map. First posted on arXiv 30 Jun 2021.
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11 of 43 references.
References · 11
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 2018Joint Status Sampling and Updating for Minimizing Age of Information in the Internet of Thingscited by 10
- 2019A Reinforcement Learning Framework for Optimizing Age-of-Information in RF-powered Communication Systemscited by 10
- 2021A Reinforcement Learning Approach to Age of Information in Multi-User Networks with HARQcited by 9
- 2019Reinforcement Learning to Minimize Age of Information with an Energy Harvesting Sensor with HARQ and Sensing Costcited by 5
- 2018A Reinforcement Learning Approach to Age of Information in Multi-User Networkscited by 3
- 2017Age Minimization in Energy Harvesting Communications: Energy-Controlled Delayscited by 2
- 2019Optimal Status Updating with a Finite-Battery Energy Harvesting Sourcecited by 2
- 2018Age-Minimal Online Policies for Energy Harvesting Sensors with Incremental Battery Rechargescited by 1
- 2020Age-of-Information with Information Source Diversity in an Energy Harvesting Systemcited by 1
- 2020Age-Aware Status Update Control for Energy Harvesting IoT Sensors via Reinforcement Learningcited by 1
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