The University of Southampton
University of Southampton Institutional Repository

A tele-traffic-aware optimal base-station deployment strategy for energy-efficient large-scale cellular networks

A tele-traffic-aware optimal base-station deployment strategy for energy-efficient large-scale cellular networks
A tele-traffic-aware optimal base-station deployment strategy for energy-efficient large-scale cellular networks
With the explosive proliferation of mobile devices and services, the user-density of large-scale cellular networks continues to increase, which results in further escalating traffic-generation. Yet, there is an urging demand for reducing the network’s energy dissipation. Hence we model the energy efficiency of large-scale cellular networks for characterizing its dependence on the base station (BS) density as well as for quantifying the impact of tele-traffic on the achievable energy efficiency under specific quality of service requirements. This allows us to match the BS deployment to the network’s tele-traffic, whilst conserving precious energy. More specifically, we formulate a practical tele-traffic-aware BS deployment problem for optimizing the network’s energy efficiency whilst satisfying the users’ maximum tolerable outage probability. This is achieved by analyzing the optimal BS-density under specific tele-traffic conditions. Furthermore, we study the energy saving potential of our optimal BS deployment strategy under diverse practical parameters and provide insights into the attainable energy savings in dense random cellular networks. Our simulation results confirm the accuracy of our analysis and verify the impact of the parameters considered on the network’s energy efficiency. Our results also demonstrate that the proposed tele-traffic-aware optimal BS deployment strategy significantly outperforms the existing approaches in terms of its energy efficiency.
2083-2095
Zhao, Guogang
66a33bee-9c30-411b-bee7-3504ec772163
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Zhao, Liqiang
3ac29793-6b4c-4bf7-a3c5-aa0950efc9db
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Zhao, Guogang
66a33bee-9c30-411b-bee7-3504ec772163
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Zhao, Liqiang
3ac29793-6b4c-4bf7-a3c5-aa0950efc9db
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Zhao, Guogang, Chen, Sheng, Zhao, Liqiang and Hanzo, Lajos (2016) A tele-traffic-aware optimal base-station deployment strategy for energy-efficient large-scale cellular networks. IEEE Access, 4, 2083-2095. (doi:10.1109/ACCESS.2016.2543210).

Record type: Article

Abstract

With the explosive proliferation of mobile devices and services, the user-density of large-scale cellular networks continues to increase, which results in further escalating traffic-generation. Yet, there is an urging demand for reducing the network’s energy dissipation. Hence we model the energy efficiency of large-scale cellular networks for characterizing its dependence on the base station (BS) density as well as for quantifying the impact of tele-traffic on the achievable energy efficiency under specific quality of service requirements. This allows us to match the BS deployment to the network’s tele-traffic, whilst conserving precious energy. More specifically, we formulate a practical tele-traffic-aware BS deployment problem for optimizing the network’s energy efficiency whilst satisfying the users’ maximum tolerable outage probability. This is achieved by analyzing the optimal BS-density under specific tele-traffic conditions. Furthermore, we study the energy saving potential of our optimal BS deployment strategy under diverse practical parameters and provide insights into the attainable energy savings in dense random cellular networks. Our simulation results confirm the accuracy of our analysis and verify the impact of the parameters considered on the network’s energy efficiency. Our results also demonstrate that the proposed tele-traffic-aware optimal BS deployment strategy significantly outperforms the existing approaches in terms of its energy efficiency.

Text
access-hanzo-2543210-proof.pdf - Accepted Manuscript
Restricted to Repository staff only
Request a copy
Text
07435256.pdf - Version of Record
Available under License Other.
Download (780kB)
Text
IEEEAccess2016.pdf - Other
Download (6MB)

More information

Accepted/In Press date: 14 March 2016
e-pub ahead of print date: 17 March 2016
Published date: 23 May 2016
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 390624
URI: http://eprints.soton.ac.uk/id/eprint/390624
PURE UUID: e31137fe-0753-4e3d-9e84-43e70ef737d0
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 05 Apr 2016 14:36
Last modified: 17 Dec 2019 02:03

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×