面向6G的信源信道联合编码传输技术OA

The demand for efficient and reliable transmission in sixth-generation(6G)semantic communications poses challenges to conventional communication architectures guided by the classical source-channel separation theorem.End-to-end optimized joint source-channel coding(JSCC)can overcome dynamic channel conditions and resource constraints,providing a new solution for 6G semantic communications.This paper first systematically reviews recent advances in JSCC and discusses the core working mechanism of end-to-end optimization.A multimodal feature-oriented analytical framework is then constructed,and the evolutionary paradigms and representative architectures of JSCC are discussed for typical sources,including text,speech,and images.In text transmission,JSCC is evolving from character-and syntax-level transmission toward semantic representation-driven transmission.In speech transmission,perceptual features are incorporated to support intelligent interaction and semantic understanding.In image transmission,the focus is shifting from pixel-level reconstruction to visual semantic preservation.Finally,key challenges for practical JSCC deployment are analyzed from the perspectives of model lightweighting,cross-modal semantic representation,robustness in dynamic environments,and joint communication-computation-network optimization.The study shows that JSCC schemes can significantly improve the perceptual quality and task effectiveness of multimodal information,and play a fundamental role in supporting the practical deployment and evolution of future 6G semantic communications.