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Existing communication systems are mainly built based on Shannon's information theory, which deliberately ignores the semantic aspects of communication. The recent iteration of wireless technology, 5G and beyond, promises to support a plethora of services enabled by carefully tailored network capabilities based on contents, requirements, as well as semantics. This has sparked significant interest in semantic communication, a novel paradigm that involves the meaning of messages in communication. In this article, we first review classic semantic communication frameworks and then summarize key challenges that hinder its popularity. We observe that some semantic communication processes such as semantic detection, knowledge modeling, and coordination can be resource-consuming and inefficient, especially for communication between a single source and a destination. We therefore propose a novel architecture based on federated edge intelligence for supporting resource-efficient semantic-aware networking. Our architecture allows each user to offload computationally intensive semantic encoding and decoding tasks to edge servers and protect its proprietary model-re-lated information by coordinating via intermediate results. Our simulation result shows that the proposed architecture can reduce resource consumption and significantly improve communication efficiency.
Shi et al. (Sun,) studied this question.