Recent Advances in Deep Learning for Channel Coding: A Survey

This paper provides a comprehensive survey of recent advances in deep learning (DL) techniques for channel coding problems. Inspired by the recent successes of DL in a variety of research domains, its applications to physical layer technologies have been extensively studied in recent years, and they...

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Vydáno v:IEEE open journal of the Communications Society Ročník 5; s. 6443 - 6481
Hlavní autoři: Matsumine, Toshiki, Ochiai, Hideki
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Channel coding
Codes
Coding
Communication systems
Decoding
Deep learning
deep learning (DL)
Error correcting codes
Error correction
Graphics processing units
low-density parity check (LDPC) codes
Machine learning
machine learning (ML)
neural network
Neural networks
Physical layer
polar codes
Reviews
Surveys
turbo codes
Wireless communication systems
ISSN:2644-125X, 2644-125X
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Shrnutí:This paper provides a comprehensive survey of recent advances in deep learning (DL) techniques for channel coding problems. Inspired by the recent successes of DL in a variety of research domains, its applications to physical layer technologies have been extensively studied in recent years, and they are expected to be a potential breakthrough in supporting the emerging use cases of the next generation wireless communication systems such as 6G. In this paper, we focus exclusively on channel coding problems and review existing approaches that incorporate advanced DL techniques into code design and channel decoding. After briefly introducing the background of recent DL techniques, we categorize and summarize a variety of approaches, including model-free and model-based DL, for the design and decoding of modern error-correcting codes, such as low-density parity check (LDPC) codes and polar codes, to highlight their potential advantages and challenges. Finally, the paper concludes with a discussion of open issues and future research directions in channel coding.
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ISSN:2644-125X
2644-125X
DOI:10.1109/OJCOMS.2024.3472094