Semantic information processing in industrial networks

被引：2
|
作者：
Yao Shengshi [1 ]
Wang Sixian [1 ]
Dai Jincheng [1 ]
Niu Kai [1 ,2 ]
Xu Wenjun [1 ,2 ]
Zhang Ping [3 ]
机构：
[1] The Key Laboratory of Universal Wireless Communications (Ministry of Education), Beijing University of Posts and Telecommunications
[2] The Peng Cheng Laboratory,Nanshan District
[3] The State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications
来源：
The Journal of China Universities of Posts and Telecommunications | 2022年 / 29卷 / 01期
基金：
中国国家自然科学基金;
关键词：
D O I：
10.19682/j.cnki.1005-8885.2022.2005
中图分类号：
TP393.09 []; TP391.1 [文字信息处理];
学科分类号：
080402 ; 081203 ; 0835 ;
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.
引用
收藏
页码：41 / 49
页数：9
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