IEEE.orgIEEE Xplore Digital Library IEEE Standards IEEE SpectrumMore Sites
T11: Application of NOMA in 6G Networks: Future Vision and Research Opportunities for Next Generation Multiple Access - VTC2021-Fall

T11: Application of NOMA in 6G Networks: Future Vision and Research Opportunities for Next Generation Multiple Access

Organizer: Zhiguo Ding, University of Manchester, UK
Organizer: Yuanwei Liu, Queen Mary University of London, UK

Abstract: User data traffic, especially large amount of video traffic and small-size internet-of-things (IoT) packets, has dramatically increased in recent years with the emergence of smart devices, smart sensors and various new applications such as virtual reality and autonomous driving. It is hence crucial to increase network capacity and user access to accommodate these bandwidth consuming applications and enhance the massive connectivity. As a prominent member of the next generation multiple access (NGMA) family, non-orthogonal multiple access (NOMA) has been recognized as a promising multiple access candidate for the sixth-generation (6G) networks. The main contents of this tutorial is to discuss the so-called “One Basic Principle plus Four New” concept. Starting with the basic NOMA principle to explore the possible multiple access techniques in non-orthogonal manner, the advantages and drawbacks of both the channel state information based successive interference cancelations (SIC) and quality-of-service based SIC are discussed. Then, the application of NOMA to meet the new 6G performance requirements, especially for massive connectivity, is explored. Furthermore, the integration of NOMA with new physical layer techniques is considered, followed by introducing new application scenarios for NOMA towards 6G. Finally, the application of machine learning in NOMA networks is investigated, ushering in the machine learning empowered NGMA era, for making multiple access in an intelligent manner for the next generation networks.


Bio: Zhiguo Ding received his B.Eng in Electrical Engineering from the Beijing University of Posts and Telecommunications in 2000, and the Ph.D degree in Electrical Engineering from Imperial College London in 2005. From Jul. 2005 to Apr. 2018, he was working in Queen’s University Belfast, Imperial College, Newcastle University and Lancaster University. Since Apr. 2018, he has been with the University of Manchester as a Professor in Communications. From Sept. 2012 to Sept. 2020, he has also been an academic visitor in Princeton University.

Dr Ding’ research interests are 5G networks, game theory, cooperative and energy harvesting networks and statistical signal processing. He has been serving as an Editor for IEEE Transactions on Communications, IEEE Transactions on Vehicular Networks, and Journal of Wireless Communications and Mobile Computing, and served as an editor for IEEE Wireless Communication Letters and IEEE Communication Letters. He was the TPC Co-Chair for the 6th IET International Conference on Wireless, Mobile & Multimedia Networks (ICWMMN2015), Symposium Chair for International Conference on Computing, Networking and Communications. (ICNC 2016), and the 25th Wireless and Optical Communication Conference (WOCC), and Co-Chair of WCNC-2013 Workshop on New Advances for Physical Layer Network Coding. He received the best paper award in IET Comm. Conf. on Wireless, Mobile and Computing, 2009 and the 2015 International Conference on Wireless Communications and Signal Processing (WCSP 2015), IEEE Communication Letter Exemplary Reviewer 2012, the EU Marie Curie Fellowship 2012-2014, IEEE TVT Top Editor 2017, 2018 IEEE Communication Society Heinrich Hertz Award, 2018 IEEE Vehicular Technology Society Jack Neubauer Memorial Award, and 2018 IEEE Signal Processing Society Best Signal Processing Letter Award. He is a Web of Science Highly Cited Researcher and a Fellow of the IEEE.

Bio: Yuanwei Liu (S’13, M’16, SM’19) received the Ph.D. degree in Electrical Engineering from the Queen Mary University of London, U.K., in 2016. He has been a Lecturer (Assistant Professor) with the School of Electronic Engineering and Computer Science, Queen Mary University of London, since 2017. He was with the Department of Informatics, King’s College London, from 2016 to 2017, where he was a Post-Doctoral Research Fellow. His research interests include non-orthogonal multiple access, 5G/6G, RIS, UAV communications, stochastic geometry, and matching theory.

Dr. Liu is the recipient of the 2020 IEEE ComSoc Outstanding Young Researcher Award IEEE ComSoc – Signal Processing and Computing for Communications (SPCC) Technical Committee. Dr. Liu is currently an Editor on the Editorial Board of the IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, the IEEE TRANSACTIONS ON COMMUNICATIONS, and IEEE COMMUNICATIONS LETTERS. He serves as the leading Guest Editor for IEEE JSAC special issue on Next Generation Multiple Access, a Guest Editor for IEEE JSTSP special issue on Signal Processing Advances for Non-Orthogonal Multiple Access in Next Generation Wireless Networks. He has served as a TPC Member for many IEEE conferences, such as GLOBECOM and ICC. He received IEEE ComSoc Outstanding Young Researcher Award for EMEA in 2020. He received the Exemplary Reviewer Certificate of IEEE WIRELESS COMMUNICATIONS LETTERS in 2015, IEEE TRANSACTIONS ON COMMUNICATIONS in 2016 and 2017, and IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS in 2017 and 2018. He has served as the Publicity Co-Chair for VTC 2019-Fall. He is the leading contributor for “Best Readings for Non-Orthogonal Multiple Access (NOMA)” and the primary contributor for “Best Readings for Reconfigurable Intelligent Surfaces (RIS)”. He serves as the chair of Special Interest Group (SIG) in Signal Processing and Computing for Communications (SPCC) Technical Committee on the topic of signal processing Techniques for next generation multiple access (NGMA), the vicechair of SIG Wireless Communications Technical Committee (WTC) on the topic of Reconfigurable Intelligent Surfaces for Smart Radio Environments (RISE), and the Tutorials and Invited Presentations Officer for Reconfigurable Intelligent Surfaces Emerging Technology Initiative.