Analog Joint Source-Channel Coding for Distributed Functional Compression using Deep Neural Networks

In this paper, we study Joint Source-Channel Coding (JSCC) for distributed analog functional compression over both Gaussian Multiple Access Channel (MAC) and AWGN channels. Notably, we propose a deep neural network based solution for learning encoders and decoders. We propose three methods of increa...

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Bibliographic Details

Published in:	2021 IEEE International Symposium on Information Theory (ISIT) pp. 2429 - 2434
Main Authors:	Saidutta, Yashas Malur, Abdi, Afshin, Fekri, Faramarz
Format:	Conference Proceeding
Language:	English
Published:	IEEE 12.07.2021
Subjects:	AWGN channels Deep learning Image coding Minimization Rate-distortion Training Upper bound
Online Access:	Get full text
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