Task-oriented Explainable Semantic Communications

doi:10.1109/TWC.2023.3269444

	Task-oriented Explainable Semantic Communications
	Shuai Ma 1; Weining Qiao 2; Youlong Wu3 ; Hang Li 4; Guangming Shi 5; Dahua Gao 5; Yuanming Shi3 ; Shiyin Li 2; Naofal Al-Dhahir 6
	2023
发表期刊	IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (IF:8.9[JCR-2023],8.6[5-Year])
ISSN	1536-1276
EISSN	1558-2248
卷号	PP 期号:99 页码:1-1
发表状态	已发表
DOI	10.1109/TWC.2023.3269444
摘要	Semantic communications utilize the transceiver computing resources to alleviate scarce transmission resources, such as bandwidth and energy. Although the conventional deep learning (DL) based designs may achieve certain transmission efficiency, the uninterpretability issue of extracted features is the major challenge in the development of semantic communications. In this paper, we propose an explainable and robust semantic communication framework by incorporating the well-established bit-level communication system, which not only extracts and disentangles features into independent and semantically interpretable features, but also only selects task-relevant features for transmission, instead of all extracted features. Based on this framework, we derive the optimal input for rate-distortion-perception theory, and derive both lower and upper bounds on the semantic channel capacity. Furthermore, based on the -variational autoencoder (-VAE), we propose a practical explainable semantic communication system design, which simultaneously achieves semantic features selection and is robust against semantic channel noise. We further design a real-time wireless mobile semantic communication proof-of-concept prototype. Our simulations and experiments demonstrate that our proposed explainable semantic communications system can significantly improve transmission efficiency, and also verify the effectiveness of our proposed robust semantic transmission scheme. IEEE
关键词	Computation theory Data mining Deep learning Electric distortion Feature extraction Radio transceivers Signal distortion Communication prototypes Communications systems Explainable semantic communication Features extraction Features selection Semantic communication Semantic communication prototype Task analysis Wireless communications
URL	查看原文
收录类别	EI
语种	英语
出版者	Institute of Electrical and Electronics Engineers Inc.
EI入藏号	20232114130238
EI主题词	Semantics
EI分类号	461.4 Ergonomics and Human Factors Engineering ; 701.1 Electricity: Basic Concepts and Phenomena ; 716.1 Information Theory and Signal Processing ; 716.3 Radio Systems and Equipment ; 721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory ; 723.2 Data Processing and Image Processing
原始文献类型	Article in Press
来源库	IEEE
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/306472
专题	信息科学与技术学院信息科学与技术学院_PI研究组_吴幼龙组信息科学与技术学院_PI研究组_石远明组
作者单位	1.Peng Cheng Laboratory, Shenzhen, China 2.School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China 3.School of Information Science and Technology, ShanghaiTech University, Shanghai, China 4.Shen zhen Research Institute of Big Data, Shenzhen, Guangdong, China 5.School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi, China 6.Electrical and Computer Engineering Department, University of Texas at Dallas, Dallas, TX, USA
推荐引用方式 GB/T 7714	Shuai Ma,Weining Qiao,Youlong Wu,et al. Task-oriented Explainable Semantic Communications[J]. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS,2023,PP(99):1-1.
APA	Shuai Ma.,Weining Qiao.,Youlong Wu.,Hang Li.,Guangming Shi.,...&Naofal Al-Dhahir.(2023).Task-oriented Explainable Semantic Communications.IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS,PP(99),1-1.
MLA	Shuai Ma,et al."Task-oriented Explainable Semantic Communications".IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS PP.99(2023):1-1.