@inproceedings{ab60020a444b48bcb451704f593fa1bd,
title = "Machine Learning and Radio Planning in the Design and Optimization of Wireless Networks",
abstract = "This paper describes the incorporation of Machine Learning in the process of designing and optimization of a Long Term Evolution network in an urban parish of Quito city performed with the help of a radio planning tool. Potential subscribers behavior within this area was extracted from an online survey. Two Machine Learning methods were applied to this data: K-Nearest Neighbors and K-Means Clustering. The former was used to identified the dissatisfied users whilst the latter to classify network users into adequate categories that were included in the design. Details of the environment were also taken account, by adding several clutter maps that include geographical information, roads, buildings and traffic patterns with the aid of a Radio Planning software that provides the propagation models and the means required for the accurate modelling, and eventually the optimization of the deployed network.",
keywords = "Atoll, K-Mean Clustering, K-Nearest Neighbors, Long Term Evolution, Machine Learning, Open Street Maps, radio planning, wireless networks",
author = "Ruiz, \{Andres Fuertes\} and Mateo Sanmart{\'i}n and Christian Criollo and \{Ren{\'e} J{\'a}tiva\}, E.",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 ; Conference date: 11-10-2022 Through 14-10-2022",
year = "2022",
doi = "10.1109/ETCM56276.2022.9935716",
language = "Ingl{\'e}s",
series = "6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Lalaleo, \{David Rivas\} and Huerta, \{Monica Karel\}",
booktitle = "6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022",
}