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Survey on Decoding Schemes of the Polar Code Using the Deep Learning

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Communications, Signal Processing, and Systems (CSPS 2022)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 873))

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Abstract

In the era of 5G Internet of everything, communications between different machines have strict requirements on latency and reliability. Due to the large amount of computations of the decoding algorithm of the polar code, the decoding time is too long, which cannot meet the low-latency system requirements. Deep learning has the ability of parallel computing, associative memory, self-organization and self-adaptation. Therefore, it is of great theoretical significance to apply deep learning to the polar code decoding algorithm. This paper reviews the development of the deep learning, and indicate that deep learning algorithms have been widely used in various fields. The traditional decoding method of the polar code is introduced, and the advantages and disadvantages of different decoding methods are compared.

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Acknowledgement

This work was supported in part by the National Natural Science Foundation of China under Grant 61801327, in part by the Doctor Fund of Tianjin Normal University under Grant 043135202-XB1711, in part by the Natural Science Foundation of Tianjin City under Grant 18JCYBJC86400, and in part by the Tianjin Higher Education Creative Team Funds Program.

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Authors and Affiliations

  1. Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, 300387, China

    Jida Yang & Yuan Liu

  2. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, 300387, China

    Yuan Liu

Authors
  1. Jida Yang
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  2. Yuan Liu
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Corresponding author

Correspondence to Yuan Liu .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. Tianjin Normal University, Tianjin, China

    Wei Wang

  3. Dalian University of Technology, Dalian, China

    Xin Liu

  4. School of Information Science and Technology, Dalian Maritime University, Dalian, China

    Zhenyu Na

  5. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Yang, J., Liu, Y. (2023). Survey on Decoding Schemes of the Polar Code Using the Deep Learning. In: Liang, Q., Wang, W., Liu, X., Na, Z., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2022. Lecture Notes in Electrical Engineering, vol 873. Springer, Singapore. https://doi.org/10.1007/978-981-99-1260-5_19

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  • DOI: https://doi.org/10.1007/978-981-99-1260-5_19

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-1259-9

  • Online ISBN: 978-981-99-1260-5

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