IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i20p3819-d274677.html
   My bibliography  Save this article

A Power Control Mean Field Game Framework for Battery Lifetime Enhancement of Coexisting Machine-Type Communications

Author

Listed:
  • Kashif Mehmood

    (Department of Information and Communication Engineering, Sejong University, Seoul 05006, Korea)

  • Muhammad Tabish Niaz

    (Department of Smart Device Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05004, Korea)

  • Hyung Seok Kim

    (Department of Information and Communication Engineering, Sejong University, Seoul 05006, Korea)

Abstract

Machine-type communications (MTC) enable the connectivity and control of a vast category of devices without human intervention. This study considers a hybrid coexisting wireless cellular network for traditional and MTC devices along with the need for an energy efficient power allocation mechanism for MTC devices. A model is presented for the interference and battery lifetime of MTC devices and a battery lifetime maximization problem is formulated. Conventional game designs are unable to address the demands of a densified user environment because of the dimensional difficulty presented when attempting to achieve a converged solution that would lead to a stable equilibrium. The MTC power control problem is modeled as a differential game and a mean field game (MFG) for massive number of MTC nodes estimates the power allocation policy with system utility defined in terms of the experienced interference and reliability. The formulated power control MFG is solved using a finite difference method and analyzed using extensive simulations. The solution provides an optimal power control strategy for MTC devices, enabling them to prolong their battery lives with the implemented energy efficient power allocation scheme.

Suggested Citation

  • Kashif Mehmood & Muhammad Tabish Niaz & Hyung Seok Kim, 2019. "A Power Control Mean Field Game Framework for Battery Lifetime Enhancement of Coexisting Machine-Type Communications," Energies, MDPI, vol. 12(20), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3819-:d:274677
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/20/3819/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/20/3819/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Olivier Guéant & Pierre Louis Lions & Jean-Michel Lasry, 2011. "Mean Field Games and Applications," Post-Print hal-01393103, HAL.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Régis Chenavaz & Corina Paraschiv & Gabriel Turinici, 2017. "Dynamic Pricing of New Products in Competitive Markets: A Mean-Field Game Approach," Working Papers hal-01592958, HAL.
    2. Amir Mosavi & Pedram Ghamisi & Yaser Faghan & Puhong Duan, 2020. "Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics," Papers 2004.01509, arXiv.org.
    3. A. Bensoussan & K. Sung & S. Yam, 2013. "Linear–Quadratic Time-Inconsistent Mean Field Games," Dynamic Games and Applications, Springer, vol. 3(4), pages 537-552, December.
    4. Amirhosein Mosavi & Yaser Faghan & Pedram Ghamisi & Puhong Duan & Sina Faizollahzadeh Ardabili & Ely Salwana & Shahab S. Band, 2020. "Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics," Mathematics, MDPI, vol. 8(10), pages 1-42, September.
    5. Ivan Cherednik, 2019. "Artificial intelligence approach to momentum risk-taking," Papers 1911.08448, arXiv.org, revised Mar 2020.
    6. Haoyang Cao & Jodi Dianetti & Giorgio Ferrari, 2021. "Stationary Discounted and Ergodic Mean Field Games of Singular Control," Papers 2105.07213, arXiv.org.
    7. Jin Ma & Eunjung Noh, 2020. "Equilibrium Model of Limit Order Books: A Mean-field Game View," Papers 2002.12857, arXiv.org, revised Mar 2020.
    8. Philippe Casgrain & Sebastian Jaimungal, 2018. "Mean-Field Games with Differing Beliefs for Algorithmic Trading," Papers 1810.06101, arXiv.org, revised Dec 2019.
    9. Michael Ludkovski & Xuwei Yang, 2017. "Mean Field Game Approach to Production and Exploration of Exhaustible Commodities," Papers 1710.05131, arXiv.org.
    10. Philippe Casgrain & Sebastian Jaimungal, 2020. "Mean‐field games with differing beliefs for algorithmic trading," Mathematical Finance, Wiley Blackwell, vol. 30(3), pages 995-1034, July.
    11. Martin Frank & Michael Herty & Torsten Trimborn, 2019. "Microscopic Derivation of Mean Field Game Models," Papers 1910.13534, arXiv.org.
    12. Pierre Gosselin & Aïleen Lotz & Marc Wambst, 2021. "A statistical field approach to capital accumulation," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(4), pages 817-908, October.
    13. Qing Tang & Fabio Camilli, 2020. "Variational Time-Fractional Mean Field Games," Dynamic Games and Applications, Springer, vol. 10(2), pages 573-588, June.
    14. Minyi Huang, 2013. "A Mean Field Capital Accumulation Game with HARA Utility," Dynamic Games and Applications, Springer, vol. 3(4), pages 446-472, December.
    15. Benazzoli, Chiara & Campi, Luciano & Di Persio, Luca, 2019. "ε-Nash equilibrium in stochastic differential games with mean-field interaction and controlled jumps," Statistics & Probability Letters, Elsevier, vol. 154(C), pages 1-1.
    16. Marcel Nutz & Yuchong Zhang, 2019. "A Mean Field Competition," Management Science, INFORMS, vol. 44(4), pages 1245-1263, November.
    17. Kalai, Ehud & Shmaya, Eran, 2018. "Large strategic dynamic interactions," Journal of Economic Theory, Elsevier, vol. 178(C), pages 59-81.
    18. Erhan Bayraktar & Yuchong Zhang, 2016. "A rank based mean field game in the strong formulation," Papers 1603.06312, arXiv.org, revised Oct 2016.
    19. Yves Achdou & Jiequn Han & Jean-Michel Lasry & Pierre-Louis Lionse & Benjamin Moll, 2022. "Income and Wealth Distribution in Macroeconomics: A Continuous-Time Approach [On the Existence and Uniqueness of Stationary Equilibrium in Bewley Economies with Production]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(1), pages 45-86.
    20. Olivier Gallay & Fariba Hashemi & Max-Olivier Hongler, 2019. "Imitation, Proximity, And Growth — A Collective Swarm Dynamics Approach," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-43, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3819-:d:274677. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.