B5G: A New Frontier for Non-Orthogonal Multiple Access
Tuesday, 8 June 2021, 14:00-15:30, Zoom Room
Speaker:
- Zhiguo Ding (University of Manchester)
- Daniel B. da Costa (National Yunlin University of Science and Technology)
- Yuanwei Liu (Queen Mary University of London)
Motivation and Context
With the current rollout of 5G, the focus of the research community is shifting towards the design of the next generation of mobile systems, e.g., 6G mobile networks. Non-orthogonal multiple access (NOMA) has been recongized as an essential enabling technology for the forthcoming 6G networks to meet the heterogeneous demands on low latency, high reliability, massive connectivity, improved fairness, and high throughput. The principle of NOMA is to encourage users for spectrum sharing, where multiple users are served in the same resource block, such as a time slot, subcarrier, or spreading code. The aim of this talk is to provide an overview of the latest research results and innovations in NOMA technologies as well as their emerging applications, including IRS-NOMA, BackCom- NOMA, NOMA-MEC, AI-empowered NOMA, etc. Future research challenges regarding NOMA in B5G and 6G are also presented.
Structure and Content
Basic Principles of NOMA- present the basics, challenges, recent progress, and open issues for
NGMA:
1) What will be different for 6G in terms of multiple access?
2) Rethinking the importance of SIC
New Requirements: Massive Connectivity for NOMA
1) QoS-based NOMA for Downlink Transmission
2) Semi-GF NOMA for Uplink Transmission
New Techniques: integration of NOMA with Emerging Physical Layer Techniques
1) OTFS-NOMA
2) Interplay between RIS and NOMA
3) THz-NOMA
4) NOMA assisted VLC
New Scenarios: Application of NOMA to Heterogeneous Scenarios
1) NOMA in Integrated Terrestrial and Aerial Networks
2) NOMA in Robotic Communications
3) NOMA assisted VR communications
4) NOMA for E-health
New Tools: Machine Learning Empowered NOMA-based Networks
1) Reinforcement Learning for NOMA-based Networks
2) Deep Learning for NOMA-based Networks
3) Other Machine Learning for NOMA-based Networks
Outlook and Discussion for research challenges and opportunities.
Zhiguo Ding
Zhiguo Ding, Ding is currently a professor at the University of Manchester. From September 2012 to September 2020, he was also an academic visitor at Princeton University. His research interests are 5G networks, signal processing, and statistical signal processing. He has been serving as an Editor for IEEE TCOM and IEEE TVT, and served as an Editor for IEEE WCL and IEEE CL. He received the EU Marie Curie Fellowship 2012–2014, IEEE TVT Top Editor 2017, the 2018 IEEE ComSoc Heinrich Hertz Award, 2018 IEEE VTS Jack Neubauer Memorial Award, and 2018 IEEE SPS Best Signal Processing Letter Award.
Daniel B. da Costa
Daniel Costa, is a Full Professor the National Yunlin University of Science and Technology (YunTech), Taiwan. He is currently Executive Editor of the IEEE Communications Letters, Area Editor of the IEEE Open Journal of the Communications Society, Area: Green, Cognitive, and Intelligent Communications and Networks, Editor at Large of the IEEE TCOM, Area: Communication Theory and Systems II, and Specialty Chief Editor of the Frontiers in Communications and Networks – Wireless Communications Section. He is also Editor of the IEEE TVT and IEEE TCCN. Prof. da Costa is the recipient of four conference paper awards. He is a World’s Top 2% Scientist from Stanford University (2020) and a Distinguished Lecturer of the IEEE Vehicular Technology Society.
Yuanwei Liu
Yuanwei Liu, has been a Lecturer (Assistant Professor) with the School of Electronic Engineering and Computer Science, Queen Mary University of London, since 2017. Dr. Liu is currently an Editor on the Editorial Board of the IEEE TWC, TCOM, and CL. 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.
