T3: Evolution of NOMA Toward Next Generation Multiple Access
Co-organizer: Zhiguo Ding, The University of Manchester, UK
Co-organizer: Yuanwei Liu, Queen Mary University of London, UK
Abstract: As more and more new mobile multimedia-rich services become available to larger audiences, there is an ever-increasing demand for higher data rates as well as larger capacity networks. This demand is to be met under the scope of next generation mobile communication systems characterized by high speed, large capacity, and good quality-of-service for millions of subscribers. To meet these requirements, numerous energy- and spectral-efficient technologies have been proposed for future networks. The sixth-generation (6G) networks need breakthroughs beyond the current 5G. The expected performance targets of 6G are: 1) The connectivity density is ten-fold larger compared to 5G; 2) The peak data rate reaches 1 terabit per second; 3) The energy efficiency is a hundred times higher than that of 5G; 4) The air interface latency decreases to 0.1 millisecond; and 5) The reliability increases to 99.99999%. To this end, highly efficient next-generation multiple access (NGMA) techniques are vital for 6G.
Non-orthogonal multiple access (NOMA) has been proposed to overcome the spectral inefficiency of orthogonal multiple access. Specifically, NOMA allows controllable interference via non-orthogonal resource allocation at the expense of a tolerable increase in receiver complexity. The signals transmitted to different users are superimposed into the same time and/or frequency band, and they are recovered with advanced receiver algorithms. Traditional NOMA schemes fail to address the new requirements of 6G. This tutorial will present our solutions about how to evolve the current NOMA to NGMA, which contributes to the Spectrum Sharing, Spectrum Management, Cognitive Radio, and Green Radio topic of VTC.
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 received the B.S. and M.S. degrees from the Beijing University of Posts and Telecommunications in 2011 and 2014, respectively, and the PhD degree in electrical engineering from the Queen Mary University of London, U.K., in 2016. He has been a Senior Lecturer (Associate Professor) with the School of Electronic Engineering and Computer Science, Queen Mary University of London, where he was a Lecturer (Assistant Professor) from 2017 to 2021. Prior to that, 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 are NOMA, RIS, Integrated sensing and communications, and machine learning. He received several research awards, including Web of Science Highly Cited Researcher 2021, the 2020 IEEE ComSoc Outstanding Young Researcher Award for EMEA, the 2020 Early Achievement Award of the IEEE ComSoc Signal Processing and Computing for Communications (SPCC) Technical Committee, the 2020 Early Achievement Award of IEEE Communication Theory Technical Committee, the 2021 IEEE ComSoc Best Young Professional Award Outstanding Nominee. Yuanwei Liu received several research recognization, including listing among the World’s Top 2% Scientists by Stanford University in 2020 and 2021, 2022 AI 2000 Most Influential Scholar Honorable Mention in Internet of Things, being ranked among Top 1% scientists in the world and Top 100 in United Kingdom in the broad field of Electronics and Electrical Engineering.
Yuanwei Liu is currently a Senior Editor of IEEE Communications Letters, an Editor of the IEEE Transactions on Wireless Communications and the IEEE Transactions on Communications. 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 served as the academic Chair for the Next Generation Multiple Access Emerging Technology Initiative. He has served as the Publicity Co-Chair for VTC 2019-Fall. He serves as the chair of Special Interest Group (SIG) in SPCC Technical Committee on signal processing Techniques for next generation multiple access, the vice-chair of SIG WTC on Reconfigurable Intelligent Surfaces for Smart Radio Environments.