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T5: Semantic Communications: Transmission beyond Shannon Paradigm - VTC2022-Spring

T5: Semantic Communications: Transmission beyond Shannon Paradigm

Co-Organizer: Geoffrey Ye Li, Imperial College London, UK
Co-Organizer: Zhijin Qin, Queen Mary University of London, UK

Abstract: Shannon and Weaver categorized communications into three levels:
• Level A. How accurately can the symbols of communication be transmitted?
• Level B. How precisely do the transmitted symbols convey the desired meaning?
• Level C. How effectively does the received meaning affect conduct in the desired way?
In the past decades, researchers primarily focus level A communications. With the development of cellular communication systems, the achieved transmission rate has been improved tens of thousands of times and the system capacity is gradually approaching to the Shannon limit. Semantic communications have been regarded as a promising direction to improve the system efficiency and reduce the data traffic so that to realize the level B or even level C communications. Semantic communications aim to realize the successful semantic information transmission that is relevant to the transmission task at the receiver. In this tutorial, we first introduce the concept of the semantic communications and a general model of it. We then detail the principles and performance metrics of semantic communications. Afterwards, we present the initial work on deep learning enabled semantic communications for different sources, multi-user semantic communication systems, and green semantic communications. Finally, we identify the research challenges in semantic communications.


Geoffrey Ye Li

Bio: Geoffrey Ye Li is currently a Chair Professor at Imperial College London, UK.  Before moving to Imperial in 2020, he was a Professor with Georgia Institute of Technology, USA, for 20 years and a Principal Technical Staff Member with AT&T Labs – Research in New Jersey, USA, for five years. His general research interests include statistical signal processing and machine learning for wireless communications. In the related areas, he has published over 600 journal and conference papers in addition to over 40 granted patents and several books. His publications have been cited over 50,000 times with an H-index over 100 and he has been recognized as a Highly Cited Researcher, by Thomson Reuters, almost every year.

Dr. Geoffrey Ye Li was awarded IEEE Fellow and IET Fellow for his contributions to signal processing for wireless communications. He won several prestigious awards from IEEE Signal Processing Society (Donald G. Fink Overview Paper Award in 2017), IEEE Vehicular Technology Society (James Evans Avant Garde Award in 2013 and Jack Neubauer Memorial Award in 2014), and IEEE Communications Society (Stephen O. Rice Prize Paper Award in 2013, Award for Advances in Communication in 2017, and Edwin Howard Armstrong Achievement Award in 2019). He also received the 2015 Distinguished ECE Faculty Achievement Award from Georgia Tech.

He has been involved in editorial activities for over 20 technical journals, including the founding Editor-in-Chief of IEEE JSAC Special Series on ML in Communications and Networking. He has organized and chaired many international conferences, including technical program vice-chair of the IEEE ICC’03, general co-chair of the IEEE GlobalSIP’14, the IEEE VTC’19 (Fall), and the IEEE SPAWC’20.


Zhijin Qin

Bio: Dr. Zhijin Qin is a Lecturer (Assistant Professor) at Queen Mary University of London since 2018. She was with Lancaster University as a Lecturer and Imperial College London as a research associate from 2016 to 2018. Her current research interest falls into semantic communications. She is serving as the guest editor of IEEE JSAC special issues on semantic communications, area editor of IEEE JSAC Series, and associate editor of IEEE Transactions on Communications. She has served as the co-chair of the 1st workshop on semantic communications at IEEE ICC 2022 and the symposium co-chair of IEEE GLOBECOM 2020/2021. She received 2017 IEEE GLOBECOM Best Paper Award, 2018 IEEE Signal Processing Society Young Author Best Paper Award, and 2021 IEEE SPCC Early Achievement Award.