Ta-Sung Lee – författare

Resource Optimization in Wireless Communications: Fundamentals, Algorithms, and Applications provides an easy-to-understand overview of the fundamentals of resource optimization, along with the latest algorithms and applications for emerging 5G, and beyond, wireless systems offering a variety of services. Additionally, it covers the principles and resource optimization of some systems expected in 6G.This book is suitable for courses in wireless communications that cover the principles of multicarrier and OFDM, the theory of resource allocation, power allocation, and subcarrier allocation, as well as the principles and optimization of OTFS, ISAC, reflective intelligent surface (RIS)-assisted mmWave, and user-centric cell-free wireless systems. It is also an ideal self-study reference text for researchers and industry engineers who wish to deepen their knowledge while researching and developing wireless systems for 6G.Provides a comprehensive introduction to resource optimization in wireless communications, laying a strong foundation for researchers developing cutting-edge resource-allocation algorithms.Includes a wide variety of resource-optimization algorithms that are ready for direct application in both research and design.Accompanied by practical examples to enhance understanding, making it ideal for self-study and hands-on practice.Explores resource optimization across a broad spectrum of 5G/6G wireless systems.Features numerous illustrations that effectively demonstrate the performance capabilities of various resource-allocation algorithms.

Resource Optimization in Wireless Communications: Fundamentals, Algorithms, and Applications provides an easy-to-understand overview of the fundamentals of resource optimization, along with the latest algorithms and applications for emerging 5G, and beyond, wireless systems offering a variety of services. Additionally, it covers the principles and resource optimization of some systems expected in 6G.This book is suitable for courses in wireless communications that cover the principles of multicarrier and OFDM, the theory of resource allocation, power allocation, and subcarrier allocation, as well as the principles and optimization of OTFS, ISAC, reflective intelligent surface (RIS)-assisted mmWave, and user-centric cell-free wireless systems. It is also an ideal self-study reference text for researchers and industry engineers who wish to deepen their knowledge while researching and developing wireless systems for 6G.- Provides a comprehensive introduction to resource optimization in wireless communications, laying a strong foundation for researchers developing cutting-edge resource-allocation algorithms.- Includes a wide variety of resource-optimization algorithms that are ready for direct application in both research and design.- Accompanied by practical examples to enhance understanding, making it ideal for self-study and hands-on practice.- Explores resource optimization across a broad spectrum of 5G/6G wireless systems.- Features numerous illustrations that effectively demonstrate the performance capabilities of various resource-allocation algorithms.

In this work from leading figures in the field, Lee, Lee, and Lin describe methods of integrated sensing and communication (ISAC) and artificial intelligence-aided radio systems to provide improved efficiency and performance to wireless users using next-generation (6G) communications systems.The authors provide the tools to master four major considerations of 6G systems: knowledge of communication systems, knowledge of radar systems, understanding of ISAC systems, and machine learning-based enhancements. Wireless Communications and Sensing: Fundamentals, Signal Processing, and Machine Learning Solutions begins by providing preliminary information regarding communication and radar systems, including descriptions of system architecture and design concepts (e.g., wireless propagation, waveforms, MIMO signal processing, and multi-user scenarios) for entry-level readers. Throughout, the authors describe novel artificial intelligence-enabled approaches to aid the design of communication and radar systems. Furthermore, this book also describes the architecture and design concepts of ISAC systems and offers an in-depth discussion of the applications of machine learning to communication, radar, and ISAC systems. Readers will be able to use their comprehensive understanding of this field to enhance ISAC system performance or aid the deployment of ISAC systems in real-world scenarios to fulfill 6G visions.This book is especially valuable for graduate and higher-level students, scholars, and engineers who want to step into the research areas of integrated sensing and communications and artificial intelligence-aided radio systems. Readers should have at least a bachelor's degree in engineering and have had some exposure to signals and systems, communication theory, and radar principles.

In this work from leading figures in the field, Lee, Lee, and Lin describe methods of integrated sensing and communication (ISAC) and artificial intelligence-aided radio systems to provide improved efficiency and performance to wireless users using next-generation (6G) communications systems.The authors provide the tools to master four major considerations of 6G systems: knowledge of communication systems, knowledge of radar systems, understanding of ISAC systems, and machine learning-based enhancements. Wireless Communications and Sensing: Fundamentals, Signal Processing, and Machine Learning Solutions begins by providing preliminary information regarding communication and radar systems, including descriptions of system architecture and design concepts (e.g., wireless propagation, waveforms, MIMO signal processing, and multi-user scenarios) for entry-level readers. Throughout, the authors describe novel artificial intelligence-enabled approaches to aid the design of communication and radar systems. Furthermore, this book also describes the architecture and design concepts of ISAC systems and offers an in-depth discussion of the applications of machine learning to communication, radar, and ISAC systems. Readers will be able to use their comprehensive understanding of this field to enhance ISAC system performance or aid the deployment of ISAC systems in real-world scenarios to fulfill 6G visions.This book is especially valuable for graduate and higher-level students, scholars, and engineers who want to step into the research areas of integrated sensing and communications and artificial intelligence-aided radio systems. Readers should have at least a bachelor's degree in engineering and have had some exposure to signals and systems, communication theory, and radar principles.