Towards Automation \& Augmentation of the Design of Schedulers for Cellular Communications Networks

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Fenton:EC,

• author = "Michael Fenton and David Lynch and David Fagan and Stepan Kucera and Holger Claussen and Michael O'Neill",
• title = "Towards Automation \& Augmentation of the Design of Schedulers for Cellular Communications Networks",
• journal = "Evolutionary Computation",
• year = "2019",
• volume = "27",
• number = "2",
• month = "Summer",
• keywords = "genetic algorithms, genetic programming, grammatical evolution, Augmentation, scheduling, heterogeneous networks",
• ISSN = "1063-6560",
• URL = "https://doi.org/10.1162/evco_a_00221",
• DOI = "doi:10.1162/evco_a_00221",
• size = "31 pages",
• abstract = "Evolutionary Computation is used to automatically evolve small cell schedulers on a realistic simulation of a 4G-LTE heterogeneous cellular network. Evolved schedulers are then further augmented by human design to improve robustness. Extensive analysis of evolved solutions and their performance across a wide range of metrics reveals evolution has uncovered a new human-competitive scheduling technique which generalises well across cells of varying sizes. Furthermore, evolved methods are shown to conform to accepted scheduling frameworks without the evolutionary process being explicitly told the form of the desired solution. Evolved solutions are shown to outperform a human-engineered state-of-the-art benchmark by up to 50percent. Finally, the approach is shown to be flexible in that tailored algorithms can be evolved for specific scenarios and corner cases, allowing network operators to create unique algorithms for different deployments, and to postpone the need for costly hardware upgrades.",
• notes = "PMID: 29528725",

}

Genetic Programming entries for Michael Fenton David Lynch David Fagan Stepan Kucera Holger Claussen Michael O'Neill

Citations