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Adaptive energy storage management in green wireless networks

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Article number7932545
Pages (from-to)1044-1048
Number of pages5
JournalIEEE SIGNAL PROCESSING LETTERS
Volume24
Issue number7
Early online date23 May 2017
DOIs
Accepted/In press15 May 2017
E-pub ahead of print23 May 2017
Published1 Jul 2017

Documents

  • Adaptive Energy Storage Management_ZHANG_Accepted15May2017_GREEN AAM

    FINAL_VERSION.pdf, 206 KB, application/pdf

    Uploaded date:18 May 2017

    Version:Accepted author manuscript

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King's Authors

Abstract

Time-varying wireless channel as well as the variability of renewable energy supply and energy prices are practically unknown in advance. To address such dynamic statistics of wireless networks, this letter develops an adaptive strategy inspired by combinatorial multiarmed bandit model for energy storage management and cost-aware coordinated load control at the base stations. The proposed strategy makes online foresighted decisions on the amount of energy to be stored in storage to minimize the average energy cost over long-time horizon. Simulation results validate the superiority of the proposed strategy over a recently proposed storage-free learning-based design.

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