Content area
Recent semantic communication methods explore effective ways to expand the communication paradigm and improve the performance of communication systems. Nonetheless, a common problem with these methods is that the essence of semantics is not explicitly pointed out and directly utilized. A new epistemology suggests that synonymity, which is revealed as the fundamental feature of semantics, guides the establishment of semantic information theory from a novel viewpoint. Building on this theoretical basis, this paper proposes a semantic arithmetic coding (SAC) method for semantic lossless compression using intuitive synonymity. By constructing reasonable synonymous mappings and performing arithmetic coding procedures over synonymous sets, SAC can achieve higher compression efficiency for meaning-contained source sequences at the semantic level and approximate the semantic entropy limits. Experimental results on edge texture map compression show a significant improvement in coding efficiency using SAC without semantic losses compared to traditional arithmetic coding, demonstrating its effectiveness.
Details
; Niu Kai 2
; Xu, Jin 1
; Zhang, Ping 3
1 Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China; [email protected] (Z.L.); [email protected] (J.X.)
2 Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China; [email protected] (Z.L.); [email protected] (J.X.), Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China
3 State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China; [email protected]