ProductAE: Toward Training Larger Channel Codes based on Neural Product Codes-Reference-Cited by-同舟云学术

ProductAE: Toward Training Larger Channel Codes based on Neural Product Codes

Published:2022-05-16 Issue: Volume: Page:
ISSN:
Container-title:ICC 2022 - IEEE International Conference on Communications
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Author:

Jamali Mohammad Vahid¹,Saber Hamid²,Hatami Homayoon²,Bae Jung Hyun²

Affiliation:

1. University of Michigan,Department of Electrical Engineering and Computer Science,Ann Arbor

2. Samsung Semiconductor, Inc.,SOC Lab

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9837954/9838246/09839215.pdf?arnumber=9839215

Reference28 articles.

1. KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning;makkuva;Proc Int Conf Mach Learn (ICML),2021

2. Learning to communicate: Channel auto-encoders, domain specific regularizers, and attention

3. Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding

4. Circular Convolutional Auto-Encoder for Channel Coding

5. Learning to decode linear codes using deep learning

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