DeepWiVe: Deep-Learning-Aided Wireless Video Transmission

We present DeepWiVe , the first-ever end-to-end joint source-channel coding (JSCC) video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, combining video compression, channel coding, and modulation steps into a single neura...

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Bibliographic Details
Published in:	IEEE journal on selected areas in communications Vol. 40; no. 9; pp. 2570 - 2583
Main Authors:	Tung, Tze-Yang, Gunduz, Deniz
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.09.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Artificial neural networks Bandwidth Bandwidths Channel allocation Coding Deep learning Distortion Frames (data processing) joint source-channel coding Machine learning Occlusion Optimization Parity check codes Resource management Video compression Video signals Video transmission Wireless communication wireless video transmission
ISSN:	0733-8716, 1558-0008
Online Access:	Get full text
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