Analysis and application research on key issues of channel coding

Research Article
Open access

Analysis and application research on key issues of channel coding

Jiatai Huang 1*
  • 1 University of Electronic and Science Technology of China    
  • *corresponding author 2020190904022@std.uestc.edu.cn
Published on 23 October 2023 | https://doi.org/10.54254/2755-2721/15/20230809
ACE Vol.15
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-021-9​
ISBN (Online): 978-1-83558-022-6

Abstract

Channel coding plays a crucial role in enhancing the reliability and efficiency of communication systems, particularly when transmission channels are disrupted by noise and interference. This paper presents an in-depth review of various channel coding techniques, their applications, and future research directions. Key topics discussed include prevalent channel coding methods, such as repetition codes, convolutional codes, LDPC codes, turbo codes, and polar codes. The paper also delves into the selection of suitable channel coding parameters and their applications in digital TV, mobile and satellite communications, unmanned aerial vehicle data links, speech communication, and underwater acoustic channels. Moreover, the paper explores the performance analysis and comparison of different channel coding techniques, shedding light on their strengths and weaknesses. Lastly, the paper identifies emerging trends and challenges in channel coding research, providing valuable insights for researchers and practitioners in the field of communication systems. By examining these techniques and future directions, this comprehensive overview aims to contribute to the development of more robust and efficient channel coding schemes for a wide range of communication applications.

Keywords:

channel coding, error correction, modulation, convolutional codes, LDPC codes, polar codes, wireless communication, IoT, 6G, machine learning

Huang,J. (2023). Analysis and application research on key issues of channel coding. Applied and Computational Engineering,15,52-59.
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References

[1]. Arora K, Singh J, Randhawa Y S. A survey on channel coding techniques for 5G wireless networks[J]. Telecommunication Systems, 2020, 73: 637-663.

[2]. Indoonundon M, Pawan Fowdur T. Overview of the challenges and solutions for 5G channel coding schemes[J]. Journal of Information and Telecommunication, 2021, 5(4): 460-483.

[3]. Kurka D B, Gündüz D. DeepJSCC-f: Deep joint source-channel coding of images with feedback[J]. IEEE Journal on Selected Areas in Information Theory, 2020, 1(1): 178-193.

[4]. Dai J, Wang S, Tan K, et al. Nonlinear transform source-channel coding for semantic communications[J]. IEEE Journal on Selected Areas in Communications, 2022, 40(8): 2300-2316.

[5]. Choi K, Tatwawadi K, Grover A, et al. Neural joint source-channel coding[C]//International Conference on Machine Learning. PMLR, 2019: 1182-1192.

[6]. Bourtsoulatze E, Kurka D B, Gündüz D. Deep joint source-channel coding for wireless image transmission[J]. IEEE Transactions on Cognitive Communications and Networking, 2019, 5(3): 567-579.

[7]. Farsad N, Rao M, Goldsmith A. Deep learning for joint source-channel coding of text[C]//2018 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, 2018: 2326-2330.

[8]. Choi K, Tatwawadi K, Grover A, et al. Neural joint source-channel coding[C]//International Conference on Machine Learning. PMLR, 2019: 1182-1192.

[9]. Zarcone R, Paiton D, Anderson A, et al. Joint source-channel coding with neural networks for analog data compression and storage[C]//2018 Data Compression Conference. IEEE, 2018: 147-156.

[10]. Balsa J, Domínguez-Bolaño T, Fresnedo Ó, et al. Transmission of still images using low-complexity analog joint source-channel coding[J]. Sensors, 2019, 19(13): 2932.

Cite this article

Huang,J. (2023). Analysis and application research on key issues of channel coding. Applied and Computational Engineering,15,52-59.

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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 5th International Conference on Computing and Data Science

ISBN：978-1-83558-021-9​(Print) / 978-1-83558-022-6(Online)
Editor：Marwan Omar, Roman Bauer, Alan Wang
Conference website: https://2023.confcds.org/
Conference date: 14 July 2023
Series: Applied and Computational Engineering
Volume number: Vol.15
ISSN：2755-2721(Print) / 2755-273X(Online)

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References

[1]. Arora K, Singh J, Randhawa Y S. A survey on channel coding techniques for 5G wireless networks[J]. Telecommunication Systems, 2020, 73: 637-663.

[2]. Indoonundon M, Pawan Fowdur T. Overview of the challenges and solutions for 5G channel coding schemes[J]. Journal of Information and Telecommunication, 2021, 5(4): 460-483.

[3]. Kurka D B, Gündüz D. DeepJSCC-f: Deep joint source-channel coding of images with feedback[J]. IEEE Journal on Selected Areas in Information Theory, 2020, 1(1): 178-193.

[4]. Dai J, Wang S, Tan K, et al. Nonlinear transform source-channel coding for semantic communications[J]. IEEE Journal on Selected Areas in Communications, 2022, 40(8): 2300-2316.

[5]. Choi K, Tatwawadi K, Grover A, et al. Neural joint source-channel coding[C]//International Conference on Machine Learning. PMLR, 2019: 1182-1192.

[6]. Bourtsoulatze E, Kurka D B, Gündüz D. Deep joint source-channel coding for wireless image transmission[J]. IEEE Transactions on Cognitive Communications and Networking, 2019, 5(3): 567-579.

[7]. Farsad N, Rao M, Goldsmith A. Deep learning for joint source-channel coding of text[C]//2018 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, 2018: 2326-2330.

[8]. Choi K, Tatwawadi K, Grover A, et al. Neural joint source-channel coding[C]//International Conference on Machine Learning. PMLR, 2019: 1182-1192.

[9]. Zarcone R, Paiton D, Anderson A, et al. Joint source-channel coding with neural networks for analog data compression and storage[C]//2018 Data Compression Conference. IEEE, 2018: 147-156.

[10]. Balsa J, Domínguez-Bolaño T, Fresnedo Ó, et al. Transmission of still images using low-complexity analog joint source-channel coding[J]. Sensors, 2019, 19(13): 2932.

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