Learning to Optimize Energy Efficiency in Energy Harvesting Wireless Sensor Networks

Debamita Ghosh, Manjesh K. Hanawal, Nikola Zlatanov

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)


We study wireless power transmission by an energy source to multiple energy harvesting nodes with the aim to maximize the energy efficiency. The source transmits energy to the nodes using one of the available power levels in each time slot and the nodes transmit information back to the energy source using the harvested energy. The source does not have any channel state information and it only knows whether a received codeword from a given node was successfully decoded or not. With this limited information, the source has to learn the optimal power level that maximizes the energy efficiency of the network. We model the problem as a stochastic Multi-Armed Bandits problem and develop an Upper Confidence Bound based algorithm, which learns the optimal transmit power of the energy source that maximizes the energy efficiency. Numerical results validate the performance guarantees of the proposed algorithm and show significant gains compared to the benchmark schemes.

Original languageEnglish
Pages (from-to)1153-1157
Number of pages5
JournalIEEE Wireless Communications Letters
Issue number6
Publication statusPublished - Jun 2021


  • Batteries
  • Energy Efficiency.
  • Energy harvesting
  • Energy Harvesting
  • Indexes
  • Information processing
  • Multi-Armed Bandits
  • Receivers
  • Transmitters
  • Wireless sensor networks
  • Wirelessly Powered Communication Network

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