상세 보기
Interoperable Semantic Communication
- Choi, Jinhyuk;
- Nam, Hyelin;
- Park, Jihong;
- Ko, Seung-Woo;
- Choi, Jinho;
- 외 2명
Citations
SCOPUS
0초록
In this chapter, we focus on AI-native transceiver designs for semantic communication (SC) and their interoperability issues with multiple users. AI-native transceivers such as deep joint source and channel coding (DeepJSCC) are inherently biased toward their training environments. Therefore, the transceivers trained under different source data and channel characteristics are difficult to decode their transmitted semantics as intended. To address this semantic misalignment problem, we put forward to distributed learning and large language model (LLM)-based solutions. © 2025 by The Institute of Electrical and Electronics Engineers, Inc.
키워드
federated learning; in-context learning; semantic communication; split learning
- 제목
- Interoperable Semantic Communication
- 저자
- Choi, Jinhyuk; Nam, Hyelin; Park, Jihong; Ko, Seung-Woo; Choi, Jinho; Bennis, Mehdi; Kim, Seong-Lyun
- 발행일
- 2024
- 유형
- Book chapter
- 저널명
- Foundations of Semantic Communication Networks
- 페이지
- 201 ~ 213