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W10: Semantic Communications - VTC2022-Fall - London/Beijing

W10: Semantic Communications

Co-chair: Yiping Duan, Tsinghua University, China
Co-chair: Qianqian Yang, Zhejiang University, China
Co-chair: Xin Deng, Beihang University, China
Co-chair: Chia-han Lee, National Yang Ming Chiao Tung University, Taiwan
Co-chair: Zhijin Qin, Tsinghua University, China

Keynote Speaker – Orhan Arikan, Bilkent University, Turkey
Keynote Speaker – Yiqun Ge, Huawei Technologies Co, China

Abstract:  As the demand for global services in communication networks increases and new application scenarios emerge, higher-level requirements for mobile communication capabilities will certainly be derived, thus driving the development of a new generation of communication technologies. Existing communication systems consider only the accurate representation and transmission of bits and symbols, ignoring semantic information. Tremendous advances in machine learning (DNNs in particular) in recent years have yielded significant insights in semantic communications. Empowering multimedia semantic representation, encoding, and transmission components through deep learning provides a viable opportunity for semantic communication. In order to develop a powerful multimedia semantic communication system with higher transmission efficiency and better quality of service, multimedia semantic representation, semantic coding, transmission, protocols, and evaluation criteria must be redesigned. This workshop aims at bringing together the researchers and practitioners interested in multimedia semantic communication and systems to address the topic, present their novel solutions, and discuss technical challenges. Topics of interest include but are not limited to:

  • Semantic information theory
  • Semantic entropy
  • Multimedia semantic compression
  • Multimedia semantic representation for multimodal data
  • Semantic coding and signal processing
  • End-to-end semantic coding and decoding
  • Semantic aided data mining, prediction and decision making
  • Machine-learning-based Image and video processing
  • Machine-learning-based Image and video transmission
  • Quality evaluation for multimedia semantic communication
  • Priori knowledge models and update methods
  • End-to-end semantic communication system for image and video
  • Network architectures and protocols for semantic communications
  • Experiments and testbeds for semantic communications
  • Semantic communications in emerging wireless networks, i.e., virtual reality, autonomous driving, unmanned aerial vehicle, among others.
  • Network Structured Fundamental Theory
  • Network communication capacity and optimization methods
  • Resource management in semantic communication systems
  • Distributed learning for semantic communication
  • Privacy-preserved semantic communications
  • Security problems and solutions in semantic communication systems
  • Theoretical limits of semantic communications

Keynote 1 Title: Semantic Signal Processing for Goal Oriented Semantic Communications 

Abstract: Semantic communications will have a significant impact on future communication networks. Recent advances in machine learning enabled real time extraction of semantic information in sensor data. In this talk we first introduce a framework for goal oriented semantic signal processing that will serve for extraction and filtering of semantic information. Unlike classical approaches where sensor data is encoded and transmitted to a processing unit in the network, in the proposed framework, semantic information in the sensor data is extracted in real time at the sensor unit. To enable efficient goal-oriented signal processing on the extracted semantic information, a hierarchical graph-based semantic language is proposed.  In this way, semantic filtering of the extracted information can be achieved at the sensor node with a dramatic reduction in the required rate of communication over the communication network.  The proposed semantic signal processing framework can easily be tailored for specific applications and goals in a diverse range of signal processing applications. To illustrate its wide range of applicability, several use cases will be introduced.


Keynote 2 Title: Semantic Communication in 6G: An Efficient Way to Sense the Physical World


Workshop Program

Tasks Beijing London Content Format
1 14:00-14:18 Technical paper presentation (Interference Identification Based on China Mobile Current Network Data) On site
2 14:18-14:36 Technical paper presentation (Investigation Of Infants’ Crying Detection In Noisy Home Scene With Deep Learning) On site
3 14:36-14:54 Technical paper presentation (Path-based Multimodal Trajectories Prediction) On site
4 14:54-15:12 Technical paper presentation (Robust Semantic Communications Against Semantic Noise) On site
5 15:12-15:30 Technical paper presentation (Semantic Communication Approach for Multi-Task Image Transmission) On site
6 15:30-16:00 Coffee break On site
7 9:00-9:18 Technical paper presentation (Semantic Communication as a Signaling Game with Correlated Knowledge Bases) On site
8 16:18-16:36 Technical paper presentation (SemKey: Boosting Secrect Key Generation for RIS-assisted Semantic Communication Systems) On site
9 16:36-16:54 Technical paper presentation (Signal Shaping for Semantic Communication Systems with A Few Message Candidates) Virtual
10 17:00-17:30 Keynote speech1 (Prof. Orhan Arikan, Bilkent University ) Virtual
11 21:00-21:45 Keynote speech2(Mr Yiqun Ge, Huawei Canada ) Virtual


Keynote Speaker Bio’s:

Orhan Arikan

Bio: Orhan Arikan was born in 1964, in Manisa, Turkey. In 1986, he received the B.Sc. degree in Electrical and Electronics Engineering from the Middle East Technical University, Ankara, Turkey. He received both the M.S. and Ph.D. degrees in Electrical and Computer Engineering from the University of Illinois Urbana-Champaign, in 1988 and 1990, respectively. Following his graduate studies, he worked for three years as a Research Scientist at Schlumberger-Doll Research Center, Ridgefield, CT, USA. During this time, he was involved in the inverse problems and fusion of multiple modality measurements. In 1993, he joined Electrical and Electronics Engineering Department of Bilkent University, Ankara, Turkey. His research interests are in the areas of semantic signal processing, statistical signal processing and remote sensing. He served as the chairman of the department in 2011-2019. Currently, he is the Dean of Engineering Faculty at Bilkent University. In 1998, He received the Distinguished Teaching Award of Bilkent University. In 2002, He received the Young Investigator Award in Engineering from Turkish Scientific and Technical Research Foundation. He has served as the Chairman of IEEE Signal Processing Society, Turkey Section in 1995-1996 and served as the President of IEEE Turkey Section in 2000-2001.

Yiqun Ge

Bio: Yiqun Ge is currently a Distinguished Research Engineer with Huawei Technologies Co., Ltd for more than 10 years. He worked on designing low-power chip for wireless applications, research on polar codes, and related 5G standardization. Currently, he is active on multiple research domains of 6G communication including channel code, machine learning, MIMO system, sensing and communication and topological information theory.  He holds an engineering bachelor degree from Shanghai Jiaotong University and master degree from ENST Bretage (IMT atlantique). Before joining Huawei, he had worked in several wireless and chip-design companies.


Co-chair’s bios:

Yiping Duan

Bio: Dr. Yiping Duan received the Ph.D. degree from the department of computer science, Xidian University, in 2016. She has been with the department of Electronic Engineering at Tsinghua university as a postdoctoral fellow from 2017 to 2019. Since April 2019, she has been an assistant research fellow in the Department of Electrical Engineering at Tsinghua University. Her research interests include wireless multimedia communication, machining learning, image and video processing. She has published 45 SCI papers, and also won two Best Paper Awards in top international conferences. In addition, she has been granted 21 invention patents including 2 U. S. patents, and received the gold award of the national invention exhibition. She was awarded the Young Elite Scientist Sponsorship Program by China Association for Science and Technology. Meanwhile, she has undertaken the sub-project of the National Key Research and Development Program of China, as well as the project of the National Natural Science Foundation of China. As one of the principal investigators, she received the first prize of the China Institute of Communications Science and Technology Invention Award, the first prize of Shanghai Technological Invention Award, and the first prize of Scientific and Technological Progress Award of the Ministry of Education, China.


Qianqian Yang

Bio: Dr. Qianqian Yang received the Ph.D. degree in electrical and electronic engineering from Imperial College London, U.K. She has held visiting positions at Centrale Supelec in 2016 and the New York University Tandon School of Engineering from 2017 to 2018. After her Ph.D., she served as a Post-Doctoral Research Associate for Imperial College London, and as a Machine Learning Researcher for Sensyne Health Plc. She is currently a Tenure-Tracked Professor with the Department of Information Science and Electronic Engineering, Zhejiang University, China. Her main research interests include AI based wireless communications techniques, network coded caching, semantic communications. She serves as a reviewer for IEEE Transactions on Information Theory, IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, etc, and has organized several workshops at conferences like ICC, WCNC, FPCC, etc..


Xin Deng

Bio: Dr. Xin Deng received the master’s degree in electrical information engineering from Beihang University, Beijing, China, in 2016, and the Ph.D. degree in electrical and electronic engineering from Imperial College London, U.K., in 2020. She is currently an Associate Professor with the Department of Cyber Science and Technology, Beihang University, Beijing, China. Her research interests include sparse coding with applications in image and video processing, machine learning, and multimodal signal processing. She was awarded the Eryl Cadwallader Davies prize by Imperial College London in 2020, and won the Shiqingyun Female Scientist award by China Society of Image and Graphics in 2021.


Chia-han Lee

Bio: Dr. Chia-han Lee received his B.S. degree from National Taiwan University, Taipei, Taiwan in 1999, M.S. degree from the University of Michigan, Ann Arbor in 2003, and Ph.D. from Princeton University in 2008, all in electrical engineering. From 1999 to 2001, he served in the R.O.C. army as a missile operations officer. From 2008 to 2009, he was a postdoctoral research associate at the University of Notre Dame, USA. Since 2010, he has been with Academia Sinica, Taipei, Taiwan, as an Assistant Research Fellow. His research interests include wire less communications and networks.


Workshop paper submissions due: 14 August 2022
Acceptance notification: 20 August 2022
Final paper submission due: 24 August 2022

To submit a paper to this workshop, please visit: