@inproceedings{57c60a7d2e1c4055a0127d79f324c448,
title = "Scheduling in heterogeneous networks using grammar-based genetic programming",
abstract = "Effective scheduling in Heterogeneous Networks is key to realising the benefits from enhanced Inter-Cell Interference Coordination. In this paper we address the problem using Grammar-based Genetic Programming. Our solution executes on a millisecond timescale so it can track with changing network conditions. Furthermore, the system is trained using only those measurement statistics that are attainable in real networks. Finally, the solution generalises well with respect to dynamic traffic and variable cell placement. Superior results are achieved relative to a benchmark scheme from the literature, illustrating an opportunity for the further use of Genetic Programming in software-defined autonomic wireless communications networks.",
keywords = "Grammar-based genetic programming, Heterogeneous networks, Scheduling",
author = "David Lynch and Michael Fenton and Stepan Kucera and Holger Claussen and Michael O{\textquoteright}Neill",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 19th European Conference on Genetic Programming, EuroGP 2016 ; Conference date: 30-03-2016 Through 01-04-2016",
year = "2016",
doi = "10.1007/978-3-319-30668-1\_6",
language = "English",
isbn = "9783319306674",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "83--98",
editor = "Mauro Castelli and James McDermott and Heywood, \{Malcolm I.\} and Ernesto Costa and Kevin Sim",
booktitle = "Genetic Programming - 19th European Conference, EuroGP 2016, Proceedings",
address = "Germany",
}