Wireless Semantic Communications

Auteur

Yao Sun, PhD, is a Lecturer at the University of Glasgow, UK. His awards and honors include the IEEE Communication Society of TOAS Best Paper Award 2019 and the IEEE IoT Journal Best Paper Award 2022. He has served as a regular reviewer and editor for numerous international journals. Lan Zhang, PhD, is an Assistant Professor in the Electrical and Computer Engineering Department at Michigan Technological University, USA. She is also an Associate Editor of IEEE Transactions on Vehicular Technologies, and has published widely on machine learning, wireless communications, and related fields. Dusit Niyato, PhD, is President's Chair Professor in the School of Computer Science and Engineering, Nanyang Technological University, Singapore. He serves as Editor-in-Chief for IEEE Communications Surveys and Tutorials, as well as an Area Editor for IEEE Transactions on Vehicular Technology and an Editor for IEEE Transactions on Wireless Communications. Muhammad Ali Imran, PhD, is a Professor in Communications Systems at the University of Glasgow, UK, Dean of Transnational Engineering Education and Dean of Graduate Studies in the College of Science and Engineering. He has published high impact articles on wireless communications and sensing subjects.

Texte du rabat

Understand the cutting-edge technology of semantic communications and its growing applications Semantic communications constitute a revolution in wireless technology, combining semantic theory with wireless communication. In a semantic communication, essential information is encoded at the source, drastically reducing the required data usage, and then decoded at the destination in such a way that all key information is recovered, even if transmission is damaged or incomplete. Enhancing the correspondence between background knowledge at source and destination can drive the data usage requirement even lower, producing ultra-efficient information exchanges with ultra-low semantic ambiguity. Wireless Semantic Communications offers a comprehensive overview of this groundbreaking field, its development, and its future application. Beginning with an introduction to semantic communications and its foundational principles, the book then proceeds to cover transceiver design and methods, before discussing use cases and future developments. The result is an indispensable resource for understanding the future of wireless communication. Readers will also find:

• Analysis of transceiver optimization methods and resource management for semantic communication
• Detailed discussion of topics including semantic encoding and decoding, Shannon information theory, and many more
• A team of editors with decades of combined experience in the study of wireless communications Wireless Semantic Communications is ideal for electrical and computing engineers and researchers, as well as industry professionals working in wireless communications.

Contenu

List of Contributions xiii

Preface xvii

1 Intelligent Transceiver Design for Semantic Communication 1
Yiwen Wang, Yijie Mao, and Zhaohui Yang

1.1 Knowledge Base 1

1.2 Source and Channel Coding 4

1.3 Multiuser SC 7

1.4 Transceiver Design for Single-Modal and Multimodal Data 13

1.5 Challenges and Future Directions 16

2 Joint Cell Association and Spectrum Allocation in Semantic Communication Networks 23
Le Xia, Yao Sun, and Muhammad Ali Imran

2.1 Introduction 23

2.2 Semantic Communication Model 26

2.3 Optimal CA and SA Solution in the PKM-Based SC-Net 32

2.4 Optimal CA and SA Solution in the IKM-Based SC-Net 35

2.5 Numerical Results and Discussions 38

2.6 Conclusions 44

3 An End-to-End Semantic Communication Framework for Image Transmission 47
Lei Feng, Yu Zhou, and Wenjing Li

3.1 Introduction 47

3.2 The End-to-End Image Semantic Communication Framework Driven by Knowledge Graph 50

3.3 Semantic Similarity Measurement 59

3.4 Simulation 62

3.5 Conclusion 63

4 Robust Semantic Communications and Privacy Protection 67
Xuefei Zhang

4.1 Motivation and Introduction 67

4.2 Robust Semantic Communication 68

4.3 Knowledge Discrepancy-Oriented Privacy Protection for Semantic Communication 75

4.4 Conclusion 84

5 Interplay of Semantic Communication and Knowledge Learning 87
Fei Ni, Bingyan Wang, Rongpeng Li, Zhifeng Zhao, and Honggang Zhang

5.1 Introduction 87

5.2 Basic Concepts and RelatedWorks 88

5.3 A KG-enhanced SemCom System 91

5.4 A KG Evolving-based SemCom System 99

5.5 LLM-assisted Data Augmentation for the KG Evolving-Based SemCom System 104

5.6 Conclusion 105

6 VISTA: A Semantic Communication Approach for Video Transmission 109
Chengsi Liang, Xiangyi Deng, Yao Sun, Runze Cheng, Le Xia, Dusit Niyato, and Muhammad Ali Imran

6.1 Introduction 109

6.2 Video Transmission Framework in VISTA 110

6.3 SLG-Based Transceiver Design in VISTA 111

6.4 Simulation Results and Discussions 116

6.5 Conclusions 120

7 Content-Aware Robust Semantic Transmission of Images over Wireless Channels with GANs 123
Xuyang Chen, Daquan Feng, Qi He, Yao Sun, and Xiang-Gen Xia

7.1 Introduction 123

7.2 System Model 124

7.3 System Architecture 127

7.4 Experimental Results 127

7.5 Conclusion 130

8 Semantic Communication in the Metaverse 133
Yijing Lin, Zhipeng Gao, Hongyang Du, Jiacheng Wang, and Jiakang Zheng

8.1 Introduction 133

8.2 RelatedWork 134

8.3 Unified Framework for SemCom in the Metaverse 137

8.4 Zero-Knowledge Proof-Based Semantic Verification 142

8.5 Diffusion Model-Based Resource Allocation 147

8.6 Simulation Results 152

8.7 Future Directions 155

8.8 Conclusion 157

9 Large Language Model-Assisted Semantic Communication Systems 163
Shuaishuai Guo, Yanhu Wang, Biqian Feng, and Chenyuan Feng

9.1 Introduction 163

9.2 SSSC Using Pretrained LLMs 165

9.3 SIAC Using Pretrained LLMs 171

9.4 Future Direction of Using LLMs: Semantic Correction 178

9.5 Conclusion 180

10 RIS-Enhanced Semantic Communication 183
Bohao Wang, Ruopeng Xu, Zhaohui Yang, and Chongwen Huang

10.1 RIS-Empowered Communications 183

10.2 Beamforming Design for RISs Enhanced Semantic Communications 184

10.3 Privacy Protection in RIS-Assisted Semantic Communication System 189

10.4 AI for RIS-Assisted Semantic Communications 191

10.5 Conclusion 195

Acronyms 195

References 196

Index 199