Non-Orthogonal Multiple Access for Massive Connectivity

ISBN-13: 9783030309749 / Angielski / Miękka / 2019 / 101 str.

Yuanwei Liu; Zhijin Qin; Zhiguo Ding

Spis treści

Introduction.- Compatibility in NOMA.- Sustainability of NOMA.- Security in NOMA.- Artificial Intelligence (AI) enabled NOMA.- Open Issues and Challenges.- Conclusion.

O autorze

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 Ph.D. degree in electrical engineering from the Queen Mary University of London, U.K., in 2016. He was with the Department of Informatics, King's College London, from 2016 to 2017, where he was a Post-Doctoral Research Fellow. He has been a Lecturer (Assistant Professor) with the School of Electronic Engineering and Computer Science, Queen Mary University of London, since 2017. His research interests include 5G wireless networks, Internet of Things, machine learning, stochastic geometry, and matching theory. He received the Exemplary Reviewer Certificate of the IEEE Wireless Communication Letters in 2015 and the IEEE Transactions on Communications and the IEEE Transactions on Wireless Communications in 2016 and 2017. He has served as a TPC Member for many IEEE conferences, such as GLOBECOM and ICC. He currently serves as an Editor of the IEEE Transactions on Communications, the IEEE Communications Letters and the IEEE Access. He is also a guest editor for IEEE JSTSP special issue on “Signal Processing Advances for Non-Orthogonal Multiple Access in Next Generation Wireless Networks”.

 

Zhijin Qin received the bachelor’s degrees from Beijing University of Posts and Telecommunications, Beijing, China, in 2012 and the Ph.D. degree from Queen Mary University of London (QMUL), London, U.K., in 2016. She joined QMUL as a Lecturer (Assistant Professor) in the School of Electronic Engineering and Computer Science since August 2018. Before that, she was with Lancaster University and Imperial College London as a Lecturer and Research Associate, respectively. Her research interests include low-power wide area networks for Internet of Things, compressive sensing and machine learning in wireless communications, and non-orthogonal multiple access. She currently serves as an Editor of the IEEE Communications Letter. She has served as a TPC member for various IEEE conferences. She received the Best Paper Award from Wireless Technology Symposium 2012, IEEE Global Communications Conference (GLOBECOM) 2017, and IEEE Signal Processing Society Young Author Best Paper Award 2018.

 

Zhiguo Ding received the B.Eng. degree 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 2005 to 2018, he was with Queen’s University Belfast, Imperial College, Newcastle University, and Lancaster University. Since 2018, he has been with the University of Manchester as a Professor in communications. From 2012 to 2018, he has also been an Academic Visitor with Princeton University. His research interests are 5G networks, game theory, cooperative and energy harvesting networks, and statistical signal processing. He received the Best Paper Award in IET ICWMC-2009 and IEEE WCSP-2014, the EU Marie Curie Fellowship 2012–2014, the Top IEEE TVT Editor 2017, the IEEE Heinrich Hertz Award 2018, and the IEEE Jack Neubauer Memorial Award 2018. He serves as an Editor for the IEEE TRANSACTIONS ON COMMUNICATIONS, the IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, and the Journal of Wireless Communications and Mobile Computing, and he was an Editor of the IEEE WIRELESS COMMUNICATION LETTERS and the IEEE COMMUNICATION LETTERS from 2013 to 2016.

Blurb

This book discusses non-orthogonal multiple access (NOMA) and the various issues in NOMA networks, including capability, sustainability, and security. This book starts from the basics and key techniques of NOMA. Subsequently, the authors discuss three critical issues in NOMA networks, including compatibility, sustainability, and security. Particularly, the authors first demonstrate the applications of NOMA in different networks including MIMO-NOMA, NOMA in heterogeneous networks, and NOMA in cognitive radio networks to show the compatibility of NOMA with various networks. Then the wireless powered NOMA networks are presented to address the sustainability issues in NOMA networks to extend the network reliability and lifetime. The security enhanced NOMA networks are discussed for single antenna case and multiple antenna case, respectively. Finally, the most recent developments on artificial intelligence (AI) enabled NOMA networks are discussed and the research challenges on NOMA to support massive number of devices are identified.

• Presents the NOMA enabled wireless networks to support massive connectivity
• Provides a framework for NOMA in the next generation of wireless communication systems
• Includes an overview of the AI-enabled NOMA networks to provide massive access opportunities with heterogeneous transmission requirements