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arXiv · 2311.12443

Knowledge Base Enabled Semantic Communication: A Generative Perspective

Jinke Ren·Zezhong Zhang·Jie Xu·Guanying Chen·Yaping Sun·Ping Zhang·Shuguang Cui
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Abstract

Semantic communication is widely touted as a key technology for propelling the 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 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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Jinke Ren, Zezhong Zhang, Jie Xu, Guanying Chen, Yaping Sun, Ping Zhang, Shuguang Cui. 2023-11-21. Knowledge Base Enabled Semantic Communication: A Generative Perspective. https://arxiv.org/abs/2311.12443

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