A genetic algorithm solution for the operation of green LTE networks with energy and environment considerations
Author | Ghazzai, Hakim |
Author | Yaacoub, Elias |
Author | Alouini, Mohamed Slim |
Author | Abu-Dayya, Adnan |
Available date | 2024-09-29T09:39:47Z |
Publication Date | 2012 |
Publication Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Resource | Scopus |
ISSN | 3029743 |
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. |
Language | en |
Publisher | Springer |
Subject | Genetic Algorithm Green Network Sleeping Strategy Smart Grid |
Type | Conference Paper |
Pagination | 512-519 |
Issue Number | PART 3 |
Volume Number | 7665 LNCS |
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QMIC Research [219 items ]