Skip to main navigation Skip to search Skip to main content

A survey on sleep mode techniques for ultra-dense networks in 5G and beyond

  • Fatima Salahdine*
  • , Johnson Opadere
  • , Qiang Liu
  • , Tao Han
  • , Ning Zhang
  • , Shaohua Wu
  • *Corresponding author for this work
  • University of North Carolina at Charlotte
  • University of Nebraska-Lincoln
  • New Jersey Institute of Technology
  • University of Windsor
  • Harbin Institute of Technology Shenzhen
  • Peng Cheng Laboratory

Research output: Contribution to journalShort surveypeer-review

Abstract

The proliferation of mobile users with an attendant rise in energy consumption mainly at the base station has requested new ways of achieving energy efficiency in cellular networks. Many approaches have been proposed to reduce the power consumption at the base stations in response to the contribution of energy cost to the increase of OPEX of the mobile operators and the rise of the carbon footprint on global climate. As a springboard to the application of sleep mode methods in ultra-dense cellular networks, this paper provides a comprehensive survey of the base station sleep mode strategies in heterogeneous mobile networks from perspectives of modeling and algorithm design. Specifically, the sleep mode enabling strategies and sleep wake-up schemes are reviewed. The base station sleep-mode techniques in ultra-dense networks are further discussed as well as the challenges and possible solutions.

Original languageEnglish
Article number108567
JournalComputer Networks
Volume201
DOIs
StatePublished - 24 Dec 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • 5G networks
  • Energy efficiency
  • Energy saving
  • Massive MIMO
  • Self-organizing networks
  • Sleep modes
  • Ultra dense networks

Fingerprint

Dive into the research topics of 'A survey on sleep mode techniques for ultra-dense networks in 5G and beyond'. Together they form a unique fingerprint.

Cite this