IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v9y2016i10p768-d78733.html
   My bibliography  Save this article

On Optimal Cell Flashing for Reducing Delay and Saving Energy in Wireless Networks

Author

Listed:
  • Jaeik Jeong

    (Department of Electronic Engineering, Sogang University, 35 Baekbeom-ro, Mapo-gu, Seoul 121-742, Korea)

  • Hongseok Kim

    (Department of Electronic Engineering, Sogang University, 35 Baekbeom-ro, Mapo-gu, Seoul 121-742, Korea)

Abstract

To save energy from cellular networks or to increase user-perceived performance, studying base station (BS) switching on–off is actively ongoing. However, many studies focus on the tradeoff between energy efficiency and user-perceived performance. In this paper, we propose a simple technique called cell flashing. Cell flashing means that base stations are turned on and off periodically and rapidly so that, when one base station is turned on, the adjacent base stations which make interferences are always off. Thus, both energy efficiency and cell edge user performances can be improved. In general, switching off base stations to save energy can lead to longer file download time (or delay) to customers. Using flow-level dynamics, we analyze average delay and energy consumption of cellular networks when cell flashing is used. We show that both of total energy consumption and average flow-level delay decrease in the case of small cells. Extensive simulations confirm that cell flashing can significantly save the energy of the base stations, e.g., by up to 25% and, at the same time, reduce the average delay by up to 75%.

Suggested Citation

  • Jaeik Jeong & Hongseok Kim, 2016. "On Optimal Cell Flashing for Reducing Delay and Saving Energy in Wireless Networks," Energies, MDPI, vol. 9(10), pages 1-13, September.
  • Handle: RePEc:gam:jeners:v:9:y:2016:i:10:p:768-:d:78733
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/9/10/768/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/9/10/768/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hojin Kim & Jaewoo So & Hongseok Kim, 2022. "Carbon-Neutral Cellular Network Operation Based on Deep Reinforcement Learning," Energies, MDPI, vol. 15(12), pages 1-13, June.
    2. Byung Moo Lee & Youngok Kim, 2016. "Design of an Energy Efficient Future Base Station with Large-Scale Antenna System," Energies, MDPI, vol. 9(12), pages 1-17, December.
    3. Byung Moo Lee & Youngok Kim, 2017. "Interference-Aware PAPR Reduction Scheme to Increase the Energy Efficiency of Large-Scale MIMO-OFDM Systems," Energies, MDPI, vol. 10(8), pages 1-16, 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:9:y:2016:i:10:p:768-:d:78733. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.