Machine Learning in Next Generation Multiple Access (NGMA)
Description
This book equips readers with the conceptual and practical knowledge they need to put into practice the design, development, and management of the next generation multiple access / non-orthogonal multiple access (NGMA/NOMA)-based network systems. The authors outline and evaluate NOMA technologies by exploiting AI/ML-based methodologies. The authors also discuss the role of NOMA in designing NGMA, and the applications/use cases of the next-generation NOMA. The book provides guidance for researchers, engineers and scientists in academia and industry working in the fields of telecom and computing, and artificial intelligence/machine learning.
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Persons
Mohammad A Matin [SM] is a professor in the Department of Electrical and Computer Engineering at North South University (NSU), where he has been since 2008. He received his B.Sc. degree in EEE from BUET, Bangladesh, his M.Sc. degree in digital communication from Loughborough University, United Kingdom, and his Ph.D. in wireless communication from Newcastle University, United Kingdom. He has published over 170 peer-reviewed journals and conference papers. He is the author/editor of 18 academic books and 22 book chapters. He serves as a member of the Editorial Boards for several international publications including IEEE Communications Magazine, IET Wireless Sensor Systems. He has received a number of prizes and scholarships including the Best Student Prize (Loughborough University), Commonwealth Scholarship, and Overseas Research Scholarship (ORS) conferred by the Committee of Vice Chancellors and Principals (CVCP) in the United Kingdom.
M. Rezwanul Mahmood received his B.S. degree in EEE from East West University, Dhaka, Bangladesh, in 2017. He has been with the Department of Electrical and Computer Engineering at North South University (NSU) as a research assistant for the last few years. He has published a few articles in top-ranked journals and book chapters since 2018. His research interests include machine learning, wireless sensor networks, and the Internet of Things.
Content
Introduction.- Activation functions.- Machine learning (ML) in non-orthogonal multiple access (NOMA).- Resource allocation in NOMA.- Towards next-generation NOMA.- Application of ML in NOMA-based networks.- Conclusion.
