19 citations · 49 across the 22 of their papers we have counts for
10 papers · 1 filter
Adaptive Source-Channel Coding for Semantic Communications
Dongxu Li, Kai Yuan, Jianhao Huang +4
Semantic communications (SemComs) have emerged as a promising paradigm for joint data and task-oriented transmissions, combining the demands for both the bit-accurate delivery and…
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…
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…
Fundamental Limitation of Semantic Communications: Neural Estimation for Rate-Distortion
Dongxu Li, Jianhao Huang, Chuan Huang +3
This paper studies the fundamental limit of semantic communications over the discrete memoryless channel. We consider the scenario to send a semantic source consisting of an observ…
Joint Task and Data Oriented Semantic Communications: A Deep Separate Source-channel Coding Scheme
Jianhao Huang, Dongxu Li, Chuan Huang +2
Semantic communications are expected to accomplish various semantic tasks with relatively less spectrum resource by exploiting the semantic feature of source data. To simultaneousl…
Toward Adaptive Semantic Communications: Efficient Data Transmission via Online Learned Nonlinear Transform Source-Channel Coding
Jincheng Dai, Sixian Wang, Ke Yang +5
The emerging field semantic communication is driving the research of end-to-end data transmission. By utilizing the powerful representation ability of deep learning models, learned…
Communication Beyond Transmitting Bits: Semantics-Guided Source and Channel Coding
Jincheng Dai, Ping Zhang, Kai Niu +3
Classical communication paradigms focus on accurately transmitting bits over a noisy channel, and Shannon theory provides a fundamental theoretical limit on the rate of reliable co…
Towards Semantic Communications: A Paradigm Shift
Kai Niu, Jincheng Dai, Shengshi Yao +4
The last seventy years have witnessed the transition of communication from Shannon's theoretical concept to current high-efficient practical systems. Classical communication system…
Nonlinear Transform Source-Channel Coding for Semantic Communications
Jincheng Dai, Sixian Wang, Kailin Tan +4
In this paper, we propose a class of high-efficiency deep joint source-channel coding methods that can closely adapt to the source distribution under the nonlinear transform, it ca…
Communication Beyond Transmitting Bits: Semantics-Guided Source and Channel Coding
Jincheng Dai, Ping Zhang, Kai Niu +3
Classical communication paradigms focus on accurately transmitting bits over a noisy channel, and Shannon theory provides a fundamental theoretical limit on the rate of reliable co…