A genetic algorithm solution for the operation of green LTE networks with energy and environment considerations

Hakim Ghazzai; Elias E. Yaacoub; Mohamed-Slim Alouini; Adnan A. Abu-Dayya

doi:10.1007/978-3-642-34487-9_62

A genetic algorithm solution for the operation of green LTE networks with energy and environment considerations

Hakim Ghazzai, Elias E. Yaacoub, Mohamed-Slim Alouini, Adnan A. Abu-Dayya

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

The Base Station (BS) sleeping strategy has become a well-known technique to achieve energy savings in cellular networks by switching off redundant BSs mainly for lightly loaded networks. Besides, the exploitation of renewable energies, as additional power sources in smart grids, becomes a real challenge to network operators to reduce power costs. In this paper, we propose a method based on genetic algorithms that decreases the energy consumption of a Long-Term Evolution (LTE) cellular network by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from the smart grid without affecting the desired Quality of Service. © 2012 Springer-Verlag.

Original language	English (US)
Title of host publication	Lecture Notes in Computer Science
Publisher	Springer Nature
Pages	512-519
Number of pages	8
ISBN (Print)	9783642344862
DOIs	https://doi.org/10.1007/978-3-642-34487-9_62
State	Published - 2012

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

UN SDGs

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

Access to Document

10.1007/978-3-642-34487-9_62

Cite this

@inproceedings{9119785b49fe4e5d820b49974db88c1a,

title = "A genetic algorithm solution for the operation of green LTE networks with energy and environment considerations",

abstract = "The Base Station (BS) sleeping strategy has become a well-known technique to achieve energy savings in cellular networks by switching off redundant BSs mainly for lightly loaded networks. Besides, the exploitation of renewable energies, as additional power sources in smart grids, becomes a real challenge to network operators to reduce power costs. In this paper, we propose a method based on genetic algorithms that decreases the energy consumption of a Long-Term Evolution (LTE) cellular network by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from the smart grid without affecting the desired Quality of Service. {\textcopyright} 2012 Springer-Verlag.",

author = "Hakim Ghazzai and Yaacoub, {Elias E.} and Mohamed-Slim Alouini and Abu-Dayya, {Adnan A.}",

note = "KAUST Repository Item: Exported on 2020-10-01",

year = "2012",

doi = "10.1007/978-3-642-34487-9_62",

language = "English (US)",

isbn = "9783642344862",

pages = "512--519",

booktitle = "Lecture Notes in Computer Science",

publisher = "Springer Nature",

}

TY - GEN

T1 - A genetic algorithm solution for the operation of green LTE networks with energy and environment considerations

AU - Ghazzai, Hakim

AU - Yaacoub, Elias E.

AU - Alouini, Mohamed-Slim

AU - Abu-Dayya, Adnan A.

N1 - KAUST Repository Item: Exported on 2020-10-01

PY - 2012

Y1 - 2012

N2 - The Base Station (BS) sleeping strategy has become a well-known technique to achieve energy savings in cellular networks by switching off redundant BSs mainly for lightly loaded networks. Besides, the exploitation of renewable energies, as additional power sources in smart grids, becomes a real challenge to network operators to reduce power costs. In this paper, we propose a method based on genetic algorithms that decreases the energy consumption of a Long-Term Evolution (LTE) cellular network by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from the smart grid without affecting the desired Quality of Service. © 2012 Springer-Verlag.

AB - The Base Station (BS) sleeping strategy has become a well-known technique to achieve energy savings in cellular networks by switching off redundant BSs mainly for lightly loaded networks. Besides, the exploitation of renewable energies, as additional power sources in smart grids, becomes a real challenge to network operators to reduce power costs. In this paper, we propose a method based on genetic algorithms that decreases the energy consumption of a Long-Term Evolution (LTE) cellular network by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from the smart grid without affecting the desired Quality of Service. © 2012 Springer-Verlag.

UR - http://hdl.handle.net/10754/564497

UR - http://link.springer.com/10.1007/978-3-642-34487-9_62

UR - http://www.scopus.com/inward/record.url?scp=84869073673&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-34487-9_62

DO - 10.1007/978-3-642-34487-9_62

M3 - Conference contribution

SN - 9783642344862

SP - 512

EP - 519

BT - Lecture Notes in Computer Science

PB - Springer Nature

ER -

A genetic algorithm solution for the operation of green LTE networks with energy and environment considerations

Abstract

ASJC Scopus subject areas

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this