LLM-Based Semantic Communication: The Way From Task-Originated To General

Document Type

Article

Source of Publication

IEEE Wireless Communications Letters

Publication Date

6-26-2025

Abstract

Semantic communication represents a paradigm shift in 6G communications, emphasizing the transmission of meaning rather than solely syntactic elements. Despite this advancement, current approaches exhibit limitations in generality, adaptability to dynamic environments, and dependence on static knowledge bases. To address these challenges, we propose a novel Large Language Model-based Semantic Communication (LLM-SemCom). LLM-SemCom incorporates three key innovations: 1) structured semantic triple representation that mitigates LLM hallucinations unlike existing unstructured approaches, 2) knowledge-base-free LLM semantic processing that adapts dynamically without static domain constraints, and 3) Retrieval-Augmented Generation-enhanced personalization that maintains semantic fidelity while enabling user-specific adaptation. Experimental results demonstrate that LLM-SemCom significantly outperforms existing methods, achieving up to a 22.7% improvement in sentence similarity while maintaining consistent performance across diverse languages and channel conditions.

ISSN

2162-2337

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Disciplines

Computer Sciences

Keywords

Hallucination, LLMs, Prompt, Semantic Communication, Semantic Triples

Scopus ID

105009650551

Indexed in Scopus

yes

Open Access

no

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