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Wireless AI


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Table of Contents

1. Principles of time reversal and effective bandwidth; Part I. Indoor Locationing and Tracking: 2. Centimeter-accuracy indoor positioning; 3. Multi-antenna approach; 4. Frequency hopping approach; 5. Decimeter-accuracy indoor tracking; Part II. Wireless Sensing and Analytics: 6. Wireless events detection; 7. Statistical learning for indoor monitoring; 8. Radio biometrics for human recognition; 9. Vital signs estimation and detection; 10. Wireless motion detection; 11. Device-free Speed estimation; Part III. Wireless Power Transfer and Energy Efficiency: 12. Time-reversal for energy efficiency; 13. Power waveforming; 14. Joint power waveforming and beamforming; Part IV. 5G Communications and Beyond: 15. Time-reversal division multiple access; 16. Combating strong-weak resonances in TRDMA; 17. Time-reversal massive multipath effect; 18. Waveforming; 19. Spatial focusing effect for networking; 20. Tunnelling effect for cloud radio access network; Part V. IoT Connections: 21. Time-reversal for IoT; 22. Heterogeneous connections for IoT.

Promotional Information

An innovative and groundbreaking text explaining how wireless AI can determine position, sense motion and vital signs, and identify events and people.

About the Author

K. J. Ray Liu is Christine Kim Eminent Professor of Information Technology in the Department of Electrical and Computer Engineering at the University of Maryland, College Park. A Highly Cited Researcher, he is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and the American Association for the Advancement of Science (AAAS), IEEE Vice President, Technical Activities, and a former President of the IEEE Signal Processing Society. He is a recipient of the 2016 IEEE Leon K. Kirchmayer Award, the IEEE Signal Processing Society 2014 Society Award, and the IEEE Signal Processing Society 2009 Technical Achievement Award. He has also co-authored several books, including Cooperative Communications and Networking (Cambridge, 2008). Beibei Wang is Chief Scientist in Wireless at Origin Wireless, Inc., and is also affiliated with the University of Maryland. She has been a recipient of the Outstanding Graduate School Fellowship, the Future Faculty Fellowship, the Dean's Doctoral Research Award from the University of Maryland, and the Overview Paper Award from the IEEE Signal Processing Society in 2015. She has co-authored Cognitive Radio Networking and Security: A Game-Theoretic View with K. J. Ray Liu (Cambridge, 2010).


'Authored by respected pioneers of this field, this book offers a generalised framework by combining physics, signal processing and machine learning to tackle many real-world applications of importance, with low complexity for practical implementation. It reveals the prospect that ambient radio can serve as a new sixth sense to help decipher the world. Written with mathematical rigour and engineering insight, this book is an excellent reference for both researchers in academia and practitioners in industry.' Wen Yonggang, Nanyang Technological University, Singapore
'Wireless AI is changing the world by enabling wireless sensing and tracking to an unprecedented level. This is the first book on major breakthroughs in this emerging field. A must read!' Sadaoki Furui, Toyota Technological Institute, Chicago
'Wireless AI is an exciting and timely book that provides the reader with the background and material needed to not only ride the wave of technological advancement but also contribute to it. Paradigm-shifting advancements, like time-reversal, cloud-RAN, motion detection and localization, and waveform designs are described in detail. Wireless AI is an innovative text that is sure to help engineers and students contribute to the rapidly evolving fields of wireless sensing and communications.' Wade Trappe, Rutgers University, New Jersey
'... an excellent book on wireless AI, with unique and comprehensive coverage, for both researchers and practitioners.' Geoffrey Li, Georgia Institute of Technology
'This book provides comprehensive coverage of extending the application of wireless networks from communication to sensing and environment analytics. The time-reversal approach is a fundamental tool for these new capabilities, and the book presents deep theoretical foundations as well as strong experimental results, with a clear and easy-to-follow presentation. A must read for students and professionals in electrical, communications, and computer engineering.' Henrique S. Malvar, Microsoft Research
''This book offers clarity on the wireless AI domain, presenting a method based on multipath analysis and machine learning for networked sensors to deliver integrated data, for purposes as diverse as biometric information, precise positioning, power transfer, 5G communications, and others ... Advanced practitioners and researchers will benefit from this integrated, principle-based approach, and graduate students specializing in the subject matter will find this book an exhaustive reference for their work.' L. Benedicenti, Choice

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