Deep Learning Based Communication Over the Air

End-to-end learning of communications systems is a fascinating novel concept that has so far only been validated by simulations for block-based transmissions. It allows learning of transmitter and receiver implementations as deep neural networks (NNs) that are optimized for an arbitrary differentiab...

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Vydané v:	IEEE journal of selected topics in signal processing Ročník 12; číslo 1; s. 132 - 143
Hlavní autori:	Dorner, Sebastian, Cammerer, Sebastian, Hoydis, Jakob, Brink, Stephan ten
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.02.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Artificial neural networks Autoencoder communication Communication systems Communications systems Computer simulation Data transmission Deep learning end-to-end learning Hardware modulation neural network Neural networks over-the-air Receivers software-defined radio Source code Synchronism Synchronization Training Transmitters
ISSN:	1932-4553, 1941-0484
On-line prístup:	Získať plný text
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