Zhiguo Ding – författare

Highly comprehensive resource investigating how next-generation multiple access (NGMA) relates to unrestricted global connection, business requirements, and sustainable wireless networksNext Generation Multiple Access is a comprehensive, state-of-the-art, and approachable guide to the fundamentals and applications of next-generation multiple access (NGMA) schemes, guiding the future development of industries, government requirements, and military utilization of multiple access systems for wireless communication systems and providing various application scenarios to fit practical case studies.The scope and depth of this book are balanced for both beginners to advanced users. Additional references are provided for readers who wish to learn more details about certain subjects. Applications of NGMA outside of communications, including data and computing assisted by machine learning, protocol designs, and others, are also covered.Written by four leading experts in the field, Next Generation Multiple Access includes information on: Foundation and application scenarios for non-orthogonal multiple access (NOMA) systems, including modulation, detection, power allocation, and resource managementNOMA's interaction with alternate applications such as satellite communication systems, terrestrial-satellite communication systems, and integrated sensingCollision resolution, compressed sensing aided massive access, latency management, deep learning enabled massive access, and energy harvestingHolographic-pattern division multiple access, over-the-air transmission, multi-dimensional multiple access, sparse signal detection, and federated meta-learning assisted resource managementNext Generation Multiple Access is an essential reference for those who are interested in discovering practical solutions using NGMA technology, including researchers, engineers, and graduate students in the disciplines of information engineering, telecommunications engineering, and computer engineering.

Machine learning explores the study and development of algorithms that can learn from and make predictions and decisions based on data. Applications of machine learning in wireless communications have been receiving a lot of attention, especially in the era of big data and IoT, where data mining and data analysis technologies are effective approaches to solving wireless system evaluation and design issues.This edited book presents current and future developments and trends in wireless communication technologies based on contributions from machine learning and other fields of artificial intelligence, including channel modelling, signal estimation and detection, energy efficiency, cognitive radios, wireless sensor networks, vehicular communications, and wireless multimedia communications. The book is aimed at a readership of researchers, engineers and students working on wireless communications and machine learning, especially those working with big data and artificial intelligence multi-disciplinary fields related to wireless communication technologies.

This book presents comprehensive coverage of current and emerging multiple access, random access, and waveform design techniques for 5G wireless networks and beyond.

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.

This book provides a comprehensive exploration of Non-Orthogonal Multiple Access (NOMA) in Heterogeneous Cellular Networks (HCNs), focusing on both theoretical foundations and practical considerations. It examines critical challenges such as non-linear high-power amplifiers (HPAs), and imperfections in successive interference cancellation (SIC). Furthermore, it presents advanced techniques including simultaneous wireless information and power transfer (SWIPT) with cooperative NOMA and the application of reconfigurable intelligent surfaces (RIS) for enhancing coverage, reliability, and energy efficiency. The authors also explore advanced research directions, including SWIPT-enabled cooperation, RIS-assisted performance analysis, and NOMA resilience under impairments suck as impulsive noise. Each chapter combines mathematical models, performance analysis, and design insights to provide a structured understanding of NOMA’s role in enabling efficient and reliable communication in next-generation networks. The primary audience for this book includes professionals in both industry and academia, who seek to apply advanced NOMA technologies to improve the performance and efficiency of HCN for 6G and beyond communication systems. As a secondary audience, graduate students in computer science, electronics and communications engineering, electrical engineering, and related disciplines will also gain both foundational knowledge and exposure to emerging research problems in this rapidly evolving field.

This book presents comprehensive coverage of current and emerging multiple access, random access, and waveform design techniques for 5G wireless networks and beyond.