@inproceedings{9cc46a7d384b4f8fb0595c7e96aee398,
title = "What can Machine Learning do for Radio Spectrum Management?",
abstract = "The opening of the unlicensed radio spectrum creates new opportunities and new challenges for communication technology that can be faced by Machine Learning techniques. In this work, we discuss the potential benefits and the challenges with reference to the recent research developments in this area. Applications go from channel estimation to Signal quality control, and from signal classification to action control. We survey Machine learning and Deep Learning algorithms with possible radio applications and highlight the corresponding challenges.",
keywords = "machine learning, radio signals, wireless communication",
author = "Ebtesam Almazrouei and Gabriele Gianini and Nawaf Almoosa and Ernesto Damiani",
note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 19th ACM symposium on QoS and Security for Wireless and Mobile Networks, Q2SWinet 2020 ; Conference date: 16-11-2020 Through 20-11-2020",
year = "2020",
month = nov,
day = "16",
doi = "10.1145/3416013.3426443",
language = "British English",
series = "Q2SWinet 2020 - Proceedings of the 16th ACM Symposium on QoS and Security for Wireless and Mobile Networks",
pages = "15--21",
booktitle = "Q2SWinet 2020 - Proceedings of the 16th ACM Symposium on QoS and Security for Wireless and Mobile Networks",
}