中国邮电高校学报(英文版) ›› 2022, Vol. 29 ›› Issue (1): 41-49.doi: 10.19682/j.cnki.1005-8885.2022.2005

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Semantic information processing in industrial networks

Yao Shengshi, Wang Sixian, Dai Jincheng, Niu Kai, Xu Wenjun, Zhang Ping   

  1. 1. The Key Laboratory of Universal Wireless Communications (Ministry of Education), Beijing University of Posts and Telecommunications, Beijing 100876, China 2. The Peng Cheng Laboratory, Nanshan District, Shenzhen 518052, China 3. The State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • 收稿日期:2021-12-13 修回日期:2022-01-27 接受日期:2022-02-03 出版日期:2022-02-26 发布日期:2022-02-28
  • 通讯作者: Corresponding author: Niu Kai E-mail:niukai@bupt.edu.cn
  • 基金资助:
    This work was supported by the Key Program of National Natural Science Foundation of China (92067202) and the National Natural Science Foundation of China (62071058).

Semantic information processing in industrial networks

Yao Shengshi, Wang Sixian, Dai Jincheng, Niu Kai, Xu Wenjun, Zhang Ping   

  1. 1. The Key Laboratory of Universal Wireless Communications (Ministry of Education), Beijing University of Posts and Telecommunications, Beijing 100876, China 2. The Peng Cheng Laboratory, Nanshan District, Shenzhen 518052, China 3. The State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2021-12-13 Revised:2022-01-27 Accepted:2022-02-03 Online:2022-02-26 Published:2022-02-28
  • Contact: Corresponding author: Niu Kai E-mail:niukai@bupt.edu.cn
  • Supported by:
    This work was supported by the Key Program of National Natural Science Foundation of China (92067202) and the National Natural Science Foundation of China (62071058).

摘要: The industrial Internet of things (industrial IoT, IIoT) aims at connecting everything, which poses severe challenges to existing wireless communication. To handle the demand for massive access in future industrial networks, semantic information processing is integrated into communication systems so as to improve the effectiveness and efficiency of data transmission. The semantic paradigm is particularly suitable for the purpose-oriented information exchanging scheme in industrial networks. To illustrate its applicability, typical industrial data are investigated, i. e. , time series and images. Simulation results demonstrate the superiority of semantic information processing, which achieves a better rate-utility tradeoff than conventional signal processing.

关键词: semantic information, semantic communication, industrial Internet of things, signal processing

Abstract: The industrial Internet of things (industrial IoT, IIoT) aims at connecting everything, which poses severe challenges to existing wireless communication. To handle the demand for massive access in future industrial networks, semantic information processing is integrated into communication systems so as to improve the effectiveness and efficiency of data transmission. The semantic paradigm is particularly suitable for the purpose-oriented information exchanging scheme in industrial networks. To illustrate its applicability, typical industrial data are investigated, i. e. , time series and images. Simulation results demonstrate the superiority of semantic information processing, which achieves a better rate-utility tradeoff than conventional signal processing.

Key words: semantic information, semantic communication, industrial Internet of things, signal processing

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