1 citations · 3 across the 11 of their papers we have counts for
12 papers
A Synonymous Variational Perspective on the Rate-Distortion-Perception Tradeoff
Zijian Liang, Kai Niu, Changshuo Wang +2
The fundamental limit of natural signal compression has traditionally been characterized by classical rate-distortion (RD) theory through the tradeoff between coding rate and recon…
A Theoretical Framework for Rate-Distortion Limits in Learned Image Compression
Changshuo Wang, Zijian Liang, Kai Niu +1
We present a novel systematic theoretical framework to analyze the rate-distortion (R-D) limits of learned image compression. While recent neural codecs have achieved remarkable em…
Way to Build Native AI-driven 6G Air Interface: Principles, Roadmap, and Outlook
Ping Zhang, Kai Niu, Yiming Liu +8
Artificial intelligence (AI) is expected to serve as a foundational capability across the entire lifecycle of 6G networks, spanning design, deployment, and operation. This article…
Synonymous Variational Inference for Perceptual Image Compression
Zijian Liang, Kai Niu, Changshuo Wang +2
Recent contributions of semantic information theory reveal the set-element relationship between semantic and syntactic information, represented as synonymous relationships. In this…
Neural Coding Is Not Always Semantic: Toward the Standardized Coding Workflow in Semantic Communications
Hai-Long Qin, Jincheng Dai, Sixian Wang +5
Semantic communication, leveraging advanced deep learning techniques, emerges as a new paradigm that meets the requirements of next-generation wireless networks. However, current s…
Rate-Distortion-Perception Controllable Joint Source-Channel Coding for High-Fidelity Generative Communications
Kailin Tan, Jincheng Dai, Zhenyu Liu +5
End-to-end image transmission has recently become a crucial trend in intelligent wireless communications, driven by the increasing demand for high bandwidth efficiency. However, ex…
Deep Generative Modeling Reshapes Compression and Transmission: From Efficiency to Resiliency
Jincheng Dai, Xiaoqi Qin, Sixian Wang +3
Information theory and machine learning are inextricably linked and have even been referred to as "two sides of the same coin". One particularly elegant connection is the essential…
DiffCom: Channel Received Signal is a Natural Condition to Guide Diffusion Posterior Sampling
Sixian Wang, Jincheng Dai, Kailin Tan +3
End-to-end visual communication systems typically optimize a trade-off between channel bandwidth costs and signal-level distortion metrics. However, under challenging physical cond…
Semantic Huffman Coding using Synonymous Mapping
Jin Xu, Kai Niu, Zijian Liang +1
Semantic communication stands out as a highly promising avenue for future developments in communications. Theoretically, source compression coding based on semantics can achieve lo…
Semantic Arithmetic Coding using Synonymous Mappings
Zijian Liang, Kai Niu, Jin Xu +1
Recent semantic communication methods explore effective ways to expand the communication paradigm and improve the system performance of the communication systems. Nonetheless, the…
A Mathematical Theory of Semantic Communication: Overview
Kai Niu, Ping Zhang
Semantic communication initiates a new direction for future communication. In this paper, we aim to establish a systematic framework of semantic information theory (SIT). First, we…
A Mathematical Theory of Semantic Communication
Kai Niu, Ping Zhang
The year 1948 witnessed the historic moment of the birth of classic information theory (CIT). Guided by CIT, modern communication techniques have approached the theoretic limitatio…