Nonlinear transform coding for semantic communications

The modular design and limited processing mechanism of traditional communication systems limit the continuous improvement of end-to-end data transmission capability.For this reason, a new nonlinear transform coding framework for semantic communications was proposed.First, an end-to-end rate distorti...

Full description

Saved in:
Bibliographic Details
Main Authors: Ping ZHANG, Jincheng DAI, Yuming ZHANG, Sixian WANG, Xiaoqi QIN, Kai NIU
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2023-04-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023087/
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The modular design and limited processing mechanism of traditional communication systems limit the continuous improvement of end-to-end data transmission capability.For this reason, a new nonlinear transform coding framework for semantic communications was proposed.First, an end-to-end rate distortion optimization criterion for semantic communication was derived based on variational theory.Based on this, a nonlinear transform was designed to extract the compact representation of source data in the semantic latent space, and variable-rate nonlinear joint source-channel coding was implemented through the guidance of variational entropy model.Experiments show that semantic nonlinear transform coding can significantly improve the end-to-end data transmission performance and robustness, and is one of the key technologies to catalyze future semantic communications.
ISSN:1000-436X