Performance Evaluation of Energy Efficiency with Sleep Mode in Ultra Dense Networks

Published

March 1, 2018

Author(s)

Hansong Xu, Wei Yu, Amirshahram Hematian, David W. Griffith, Nada T. Golmie

Abstract

Massively deployed mobile devices and an extensive volume of data traffic will immensely increase demand on future wireless networks. The Ultra Dense Network (UDN), as one of key techniques in 5G, is expected to support massive connections and offload the intense volume of data traffic. One main feature of UDN is the high-density deployment of small cell Base Stations (BSs) to boost the support of massive traffic volume. Nonetheless, the small cell BS density raises the issue of energy efficiency, especially when data transmission is not frequent in a certain time or location. One effective approach to reduce energy consumption is to leverage the BS sleep mode, which disables energy hungry functions and components. Extensive research has been conducted to improve energy efficiency in networks such as Heterogeneous Network (HetNet), but such investigations have been rare for UDN. To this end, in this paper we examine existing energy efficiency schemes, and introduce schemes in the context of UDN. Furthermore, we implement and compare various representative schemes in the UDN scenario via simulation. Through extensive experimentation, we demonstrate the effectiveness and limitations of the numerous schemes, comparing energy consumption and end-to-end delay performance. Our results indicate that the newly introduced schemes outperform existing schemes, with respect to reducing energy consumption and end-to-end delay.

Proceedings Title

International Conference on Computing, Networking and Communications (ICNC 2018)

Conference Dates

March 5-8, 2018

Conference Location

Lahaina, HI, US

Pub Type

Conferences

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DOI Link

Citation

Xu, H. , Yu, W. , Hematian, A. , Griffith, D. and Golmie, N. (2018), Performance Evaluation of Energy Efficiency with Sleep Mode in Ultra Dense Networks, International Conference on Computing, Networking and Communications (ICNC 2018), Lahaina, HI, US, [online], https://doi.org/10.1109/ICCNC.2018.8390302 (Accessed May 9, 2025)