Power Control in Internet of Drones by Deep Reinforcement Learning

Jingjing Yao, Nirwan Ansari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Internet of Drones (IoD) employs drones as the internet of things (IoT) devices to provision applications such as traffic surveillance and object tracking. Data collection service is a typical application where multiple drones are deployed to collect information from the ground and send them to the IoT gateway for further processing. The performance of IoD networks is constrained by drones' battery capacities, and hence we utilize both energy harvesting technologies and power control to address this limitation. Specifically, we optimize drones' wireless transmission power at each time epoch in energy harvesting aided time-varying IoD networks for the data collection service with the objective to minimize the average system energy cost. We then formulate a Markov Decision Process (MDP) model to characterize the power control process in dynamic IoD networks, which is then solved by our proposed model-free deep actor-critic reinforcement learning algorithm. The performance of our algorithm is demonstrated via extensive simulations.

Original languageEnglish (US)
Title of host publication2020 IEEE International Conference on Communications, ICC 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728150895
DOIs
StatePublished - Jun 2020
Event2020 IEEE International Conference on Communications, ICC 2020 - Dublin, Ireland
Duration: Jun 7 2020Jun 11 2020

Publication series

NameIEEE International Conference on Communications
Volume2020-June
ISSN (Print)1550-3607

Conference

Conference2020 IEEE International Conference on Communications, ICC 2020
Country/TerritoryIreland
CityDublin
Period6/7/206/11/20

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Keywords

  • Power control
  • actor-critic
  • deep reinforcement learning
  • energy harvesting
  • internet of drones (IoD)
  • quality of service (QoS)

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