T9: Semantic Communications: Joint coding, Transmission and Applications

Organizer: Wei Chen, Beijing Jiaotong University, China
Organizer: Zhijin Qin, Tsinghua University, China

Abstract: In this tutorial, we will first introduce the concept of the semantic communication and highlight its key difference from typical communications. We then detail the general model and performance metrics of semantic communications. Afterwards, we will present the latest work on deep learning enabled semantic communications for text, speech, and image transmission. By employing a semantic encoder and channel encoder and dealing with their jointly design, the semantic communication system could achieve a significant performance improvement in terms of semantic information exchange. Besides, those massive amount of data are usually high dimensional, multi modal, distributed and required to be exchanged in an efficient, effective, and timely manner. We will provide a unified semantic communication structure to support multi modal data transmission for multi-tasks.

Organizer’s bios:

Dr. Wei Chen is a Professor at Beijing Jiaotong University, China. He received the B.Eng. degree and M.Eng. degree from Beijing University of Posts and Telecommunications, China, in 2006 and 2009, respectively, and the Ph.D. degree in Computer Science from the University of Cambridge, UK, in 2013. Later, he was a Research Associate with the Computer Laboratory, University of Cambridge from 2013 to 2016. His current research interests include semantic communications, AL/ML for PHY and sparse signal processing. He was a recipient of the 2013 IET Wireless Sensor Systems Premium Award, the 2017 International Conference on Computer Vision (ICCV) Young Researcher Award, the 2019 CCF-Tencent Rhino Bird Innovation Award, the 2020 IWCMC 5G-EWNAT Workshop Best Paper Award, and 2023 IEEE/CIC ICCC Best Paper Award. He serves as the lead guest editor for IEEE JSTSP Special Issue on Intelligent Signal Processing and Learning for Next Generation Multiple Access.

Dr. Zhijin Qin is an Associate Professor at Tsinghua University, China. She was with Queen Mary University of London and Lancaster University as a lecturer as well as with Imperial College London as a research associate from 2016 to 2022. She obtained her PhD degree in 2016 and the bachelor degree in 2012. Her research interests include semantic communications and sparse signal processing in wireless communications. She serves as an area editor of IEEE JSAC Series on Machine learning in Communications and Networks, an associate editor of IEEE Transactions on Communications, IEEE Transactions on Cognitive Communications and Networking, and IEEE Communications Letters. Dr Qin has served as the symposium cochair for IEEE VTC Fall 2019 and IEEE Globecom 2020/2021. She received the 2017 IEEE Globecom Best Paper Award, the 2018 IEEE Signal Processing Society Young Author Best Paper Award, the 2021 IEEE Communications Society SPCC Early Achievement Award, the 2022 IEEE Communications Society Fred W. Ellersick Prize, the 2023 IEEE ICC Best Paper Award, and 2023 IEEE Signal Processing Society Best Paper Award.