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Wireless Personal Communications

Erschienen in:

21.03.2019

Machine Learning for Wireless Communication Channel Modeling: An Overview

verfasst von: Saud Mobark Aldossari, Kwang-Cheng Chen

Erschienen in: Wireless Personal Communications | Ausgabe 1/2019

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Abstract

Channel modeling is fundamental to design wireless communication systems. A common practice is to conduct tremendous amount of channel measurement data and then to derive appropriate channel models using statistical methods. For highly mobile communications, channel estimation on top of the channel modeling enables high bandwidth physical layer transmission in state-of-the-art mobile communications. For the coming 5G and diverse Internet of Things, many challenging application scenarios emerge and more efficient methodology for channel modeling and channel estimation is very much needed. In the mean time, machine learning has been successfully demonstrated efficient handling big data. In this paper, applying machine learning to assist channel modeling and channel estimation has been introduced with evidence of literature survey.

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Titel: Machine Learning for Wireless Communication Channel Modeling: An Overview
verfasst von: Saud Mobark Aldossari
Kwang-Cheng Chen
Publikationsdatum: 21.03.2019
Verlag: Springer US
Erschienen in: Wireless Personal Communications / Ausgabe 1/2019
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI: https://doi.org/10.1007/s11277-019-06275-4

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