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Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning

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  • Insoo Sohn
  • Huaping Liu
  • Nirwan Ansari

Abstract

An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction.

Suggested Citation

  • Insoo Sohn & Huaping Liu & Nirwan Ansari, 2015. "Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-13, July.
    • Handle: RePEc:plo:pone00:0132997
    DOI: 10.1371/journal.pone.0132997
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    References listed on IDEAS

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    1. Sergiu Hart & Andreu Mas-Colell, 2013. "A Simple Adaptive Procedure Leading To Correlated Equilibrium," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 2, pages 17-46, World Scientific Publishing Co. Pte. Ltd..
    2. Arent, Douglas J. & Wise, Alison & Gelman, Rachel, 2011. "The status and prospects of renewable energy for combating global warming," Energy Economics, Elsevier, vol. 33(4), pages 584-593, July.
    3. Sergiu Hart & Andreu Mas-Colell, 2013. "A General Class Of Adaptive Strategies," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 3, pages 47-76, World Scientific Publishing Co. Pte. Ltd..
    4. Insoo Sohn, 2015. "Access Point Selection Game with Mobile Users Using Correlated Equilibrium," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-13, March.
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