语义通讯——智能时代的产物<sup>*</sup>

doi:10.16451/j.cnki.issn1003-6059.201801008

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Abstract

Communication technology develops greatly, especially in source and channel coding, modulation mechanisms and ultra-wideband communications. From the aspect of signal processing, current technologies have already approached the Shannon capacity. Directions for future researches in traditional data and signal transmission-based communication industry become unclear. According to the recent state-of-the-art artificial intelligence technologies and their influences on the revolution of the communication industry, a new communication mechanism, namely semantic communications, is proposed. Compared with the traditional communication technology based on pattern transmission, the key point of semantic communications is idea-passing communication, and it can also be referred to as content transmission. In such a revolutionary communication mechanism, the transmission is conducted upon ideas instead of data through the construction of a certain knowledge library. The error tolerance of the channel can also be improved via the matching between the idea transmitter and receiver. It could be considered as the artificial intelligence induced communication with its true meaning since it is a brain-resembling communication mechanism. The introduced brain-resembling communication mechanism based on idea-passing significantly reduces the data amount to be transmitted, and it is an efficient way to address the challenge to the communication industry due to the arrival of big data era. In this paper, the tentative idea of semantic communications is presented and the fundamental elements, semantic coding and decoding, future research directions and major challenges in semantic communications are discussed.

Key words： Semantic Communications Semantic Elements Intelligence Communications Idea-Passing Interaction Semantic Networks

Received: 25 September 2017

About author:: SHI GuangmingCorresponding author, Ph.D., professor. His research interests include compressive sensing theory and its applications, brain understanding and brain-machine communications, deep neural networks. LI Yingyu, Ph.D. candidate. Her research interests include big data collection and analysis, distributed data offloading and resource allocation in wireless communication networks as well as internet of things.XIE Xuemei, Ph.D., professor. Her research interests include video and image processing, deep learning and compressive sensing.

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Cite this article:

SHI Guangming,LI Yingyu,XIE Xuemei. Semantic Communications: Outcome of the Intelligence Era[J]. , 2018, 31(1): 91-99.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201801008 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I1/91

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