Distributed energy cooperation for energy harvesting nodes using reinforcement learning

Wei Ting Lin, I. Wei Lai, Chia-Han Lee

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

3 Scopus citations

Abstract

Wireless communication with nodes capable of harvesting energy emerges as a new technology challenge. In this paper, we investigate the problem of utilizing energy cooperation among energy-harvesting transmitters to maximize the data rate performance. We consider a general framework which can be applied to either cellular networks with base station energy cooperation through wired power grid or sensor networks with transmitting node energy cooperation through wireless power transfer. We model this energy cooperation problem as an infinite horizon Markov decision process (MDP), which can be optimally solved by the value iteration algorithm. Since the optimal value iteration algorithm has high complexity and requires non-causal information, we propose a distributed algorithm by using reinforcement learning and splitting the MDP into several small MDPs, each associated with a transmitter. Simulation results demonstrate the effectiveness of the proposed distributed energy cooperation algorithm.

Original languageEnglish
Title of host publication2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1584-1588
Number of pages5
ISBN (Electronic)9781467367820
DOIs
StatePublished - 1 Dec 2015
Event26th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2015 - Hong Kong, China
Duration: 30 Aug 20152 Sep 2015

Publication series

NameIEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Volume2015-December

Conference

Conference26th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2015
CountryChina
CityHong Kong
Period30/08/152/09/15

Fingerprint Dive into the research topics of 'Distributed energy cooperation for energy harvesting nodes using reinforcement learning'. Together they form a unique fingerprint.

  • Cite this

    Lin, W. T., Lai, I. W., & Lee, C-H. (2015). Distributed energy cooperation for energy harvesting nodes using reinforcement learning. In 2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2015 (pp. 1584-1588). [7343551] (IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC; Vol. 2015-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PIMRC.2015.7343551