Neural Network Detection of Data Sequences in Communication Systems

We consider detection based on deep learning, and show it is possible to train detectors that perform well without any knowledge of the underlying channel models. Moreover, when the channel model is known, we demonstrate that it is possible to train detectors that do not require channel state inform...

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Veröffentlicht in:	IEEE transactions on signal processing Jg. 66; H. 21; S. 5663 - 5678
Hauptverfasser:	Farsad, Nariman, Goldsmith, Andrea
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.11.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Bit error rate Channel estimation Channel models Communication systems deep learning detection Detection algorithms Detectors Error detection free-space optical communication Machine learning molecular communication Neural networks optical communication Performance evaluation Receivers Recurrent neural networks Sensors supervised learning
ISSN:	1053-587X, 1941-0476
Online-Zugang:	Volltext
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