Knowledge Base Enabled Semantic Communication: A Generative Perspective

Semantic communication is widely touted as a key technology for propelling sixth-generation (6G) wireless networks. However, providing effective semantic representation is quite challenging in practice. To address this issue, this article takes a crack at exploiting a semantic knowledge base (KB) to usher in a new era of generative semantic communication. Via semantic KB, source messages can be characterized in low-dimensional subspaces without compromising their desired meanings, thus significantly enhancing the communication efficiency. The fundamental principle of semantic KB is first introduced, and a generative semantic communication architecture is developed by presenting three sub-KBs, namely source, task, and channel KBs. Then, the detailed construction approaches for each sub-KB are described, followed by their utilization in terms of semantic coding and transmission. A case study is also provided to showcase the superiority of generative semantic communication over conventional syntactic communication and classical semantic communication. In a nutshell, this article establishes a scientific foundation for the exciting uncharted frontier of generative semantic communication.

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Publication Details

Journal
IEEE Wireless Communications
Published
2024-08-01
DOI
https://doi.org/10.1109/mwc.001.2300553
Citations
34
Primary Topic
Wireless Signal Modulation Classification
Type
article
Field-Weighted Citation Impact
11.81

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article

Knowledge Base Enabled Semantic Communication: A Generative Perspective

Jie Xu, Shuguang Cui, Jinke Ren, Guanying Chen et al.
34 citations
IEEE Wireless Communications
Wireless Signal Modulation Classification
11.81
article

Knowledge Base Enabled Semantic Communication: A Generative Perspective

Jie Xu, Shuguang Cui, Jinke Ren, Guanying Chen, Ping Zhang, Ya‐Ping Sun, Zezhong Zhang
article en
34 citations

Abstract

Semantic communication is widely touted as a key technology for propelling sixth-generation (6G) wireless networks. However, providing effective semantic representation is quite challenging in practice. To address this issue, this article takes a crack at exploiting a semantic knowledge base (KB) to usher in a new era of generative semantic communication. Via semantic KB, source messages can be characterized in low-dimensional subspaces without compromising their desired meanings, thus significantly enhancing the communication efficiency. The fundamental principle of semantic KB is first introduced, and a generative semantic communication architecture is developed by presenting three sub-KBs, namely source, task, and channel KBs. Then, the detailed construction approaches for each sub-KB are described, followed by their utilization in terms of semantic coding and transmission. A case study is also provided to showcase the superiority of generative semantic communication over conventional syntactic communication and classical semantic communication. In a nutshell, this article establishes a scientific foundation for the exciting uncharted frontier of generative semantic communication.

IEEE Wireless CommunicationsVol. 31(4)
Beijing University of Posts and Telecommunications (CN), Chinese University of Hong Kong, Shenzhen (CN), Peng Cheng Laboratory (CN)
National Natural Science Foundation of China, Shenzhen Science and Technology Innovation Program
Openalex Percentile: Top 1%
Wireless Signal Modulation Classification
11.81
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Knowledge Base Enabled Semantic Communication: A Generative Perspective — Jie Xu, Shuguang Cui, et al. · IEEE Wireless Communications (2024) | TGRS Research Map | TGRS