''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
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.