@inproceedings{de3088f821e3469589095aebae51dec0,
title = "Impulse noise detection in OFDM communication system using machine learning ensemble algorithms",
abstract = "An impulse noise detection scheme employing machine learning (ML) algorithm in Orthogonal Frequency Division Multiplexing (OFDM) is investigated. Four powerful ML{\textquoteright}s multi-classifiers (ensemble) algorithms (Boosting (Bos), Bagging (Bag), Stacking (Stack) and Random Forest (RF)) were used at the receiver side of the OFDM system to detect if the received noisy signal contained impulse noise or not. The ML{\textquoteright}s ensembles were trained with the Middleton Class A noise model which was the noise model used in the OFDM system. In terms of prediction accuracy, the results obtained from the four ML{\textquoteright}s Ensembles techniques show that ML can be used to predict impulse noise in communication systems, in particular OFDM.",
keywords = "Bagging, Boosting, Ensemble, OFDM and impulse noise, Prediction, Random forest, Stacking",
author = "Hasan, {Ali N.} and Thokozani Shongwe",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2016, International Conference on Computational Intelligence in Security for Information Systems, CISIS 2016 and International Conference on European Transnational Education, ICEUTE 2016 ; Conference date: 19-10-2016 Through 21-10-2016",
year = "2017",
doi = "10.1007/978-3-319-47364-2_9",
language = "English",
isbn = "9783319473635",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "85--91",
editor = "Lopez-Guede, {Jose Manuel} and Alvaro Herrero and Hector Quintian and Manuel Grana and Oier Etxaniz and Emilio Corchado",
booktitle = "International Joint Conference, SOCO 2016-CISIS 2016-ICEUTE 2016, Proceedings",
address = "Germany",
}