This book introduces the development of self-interference (SI)-cancellation techniques for full-duplex wireless communication systems. The authors rely on estimation theory and signal processing to develop SI-cancellation algorithms by generating an estimate of the received SI and subtracting it from the received signal. The authors also cover two new SI-cancellation methods using the new concept of active signal injection (ASI) for full-duplex MIMO-OFDM systems. The ASI approach adds an appropriate cancelling signal to each transmitted signal such that the combined signals from transmit antennas attenuate the SI at the receive antennas. The authors illustrate that the SI-pre-cancelling signal does not affect the data-bearing signal. This book is for researchers and professionals working in wireless communications and engineers willing to understand the challenges of deploying full-duplex and practical solutions to implement a full-duplex system. Advanced-level students in electrical engineering and computer science studying wireless communications will also find this book useful as a secondary textbook.

Many wireless systems could benefit from the ability to transmit and receive on the same frequency at the same time, which is known as In-Band Full-Duplex (IBFD). This technology could lead to enhanced spectral efficiency for future wireless networks, such as fifth-generation New Radio (5G NR) and beyond, and could enable capabilities and applications that were previously considered impossible, such as IBFD with phased array systems. In this exciting new book, experts from industry, academic, and federal research institutions discuss the various approaches that can be taken to suppress the inherent self-interference that is generated in IBFD systems. Both static and adaptive techniques that span across the propagation, analog and digital domains are presented. Details and measured results that encompass high-isolation antenna designs, RF, and photonic cancellation as well as signal processing approaches, which include beamforming and linear/non-linear equalization are detailed. Throughout this book, state-of-the-art IBFD systems that utilize these technologies will be provided as practical examples for various applications. Expert IBFD perspectives from multiple research organizations and companies, which would provide readers with the most accurate state-of-the-art approaches. This is the first book that dives into both the techniques that make IBFD systems possible as well as several different applications that use IBFD technology.

A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

Learn about the key technologies and state of the art in research for full-duplex communications with this comprehensive guide.

This textbook takes a unified view of the fundamentals of wireless communication and explains cutting-edge concepts in a simple and intuitive way. An abundant supply of exercises make it ideal for graduate courses in electrical and computer engineering and it will also be of great interest to practising engineers.

This book focuses on the multidisciplinary state-of-the-art of full-duplex wireless communications and applications. Moreover, this book contributes with an overview of the fundamentals of full-duplex communications, and introduces the most recent advances in self-interference cancellation from antenna design to digital domain. Moreover, the reader will discover analytical and empirical models to deal with residual self-interference and to assess its effects in various scenarios and applications. Therefore, this is a highly informative and carefully presented book by the leading scientists in the area, providing a comprehensive overview of full-duplex technology from the perspective of various researchers, and research groups worldwide. This book is designed for researchers and professionals working in wireless communications and engineers willing to understand the challenges and solutions full-duplex communication so to implement a full-duplex system.