Machine Learning for Wireless Communication
Springer International Publishing (Verlag)
978-3-031-94116-0 (ISBN)
This book covers the basic principles of wireless communication while delving into the fundamentals of machine learning, including supervised and unsupervised learning, deep learning, and reinforcement learning. The authors provide real-world examples and case studies to illustrate the use of machine learning in wireless communication applications such as channel estimation, mobility prediction, resource allocation, and beamforming. This book is an essential resource for researchers, engineers, and students interested in understanding and applying machine learning techniques in the context of wireless communication systems.
Dr. Rohit Thanki is a seasoned AI researcher and data scientist with over 12 years of scientific research experience and over 5 years in AI-powered MedTech startups. He currently serves as a Technical Lead & Data Scientist at DetMedX, Wolfsburg, Germany, where he leads the development of innovative, AI-driven healthcare solutions. Before this, he held leadership roles such as Head of R&D at Prognica Labs, Dubai, and worked as a Software Consultant at Ennoventure Technologies, India.
He earned his Ph.D. in biometric security and data encryption from C. U. Shah University, Gujarat, India. He has since mentored several Ph.D. and master's research students across institutions in Germany and India. His expertise spans medical image analysis, artificial intelligence, machine learning, computer vision, digital watermarking, content security, and signal processing. He has led AI projects involving a variety of medical imaging modalities, including X-ray, MRI, CT, ultrasound, and mammography.
Stanford University and Elsevier recognized Dr. Thanki among the Top 2% of AI and image processing scientists in 2024. He has authored over 20 technical books (16 of which are indexed in Scopus) and published more than 100 research articles in reputed journals and conferences indexed in Scopus and the Web of Science. His work has been cited over 2,400 times and has an h-index of 23.
Dr. Thanki is an active Senior Member of IEEE and the German AI Association. He serves on editorial boards for several international journals, including BMC Digital Health (Springer Nature) and PLOS ONE. He is also a frequent reviewer for top-tier journals such as IEEE Access, Pattern Recognition, and the IEEE Journal of Biomedical and Health Informatics.
His curre
Introduction.- Basic of Wireless Communication and Machine Learning.- Machine Learning Algorithms for Channel Prediction.- Machine Learning Algorithms for Resource Allocation.- Machine Learning Algorithms for Beamforming.- Machine Learning Algorithms for Mobility Prediction.- Practical Example of ML used in Wireless Communication.- Conclusion.
| Erscheinungsdatum | 13.06.2025 |
|---|---|
| Reihe/Serie | Synthesis Lectures on Communications |
| Zusatzinfo | XIV, 119 p. 53 illus., 48 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 168 x 240 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Netzwerke |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Nachrichtentechnik | |
| Schlagworte | Beamforming • Channel Prediction • machine learning for wireless communication • ML Algorithms • mobility prediction • Resource Allocation |
| ISBN-10 | 3-031-94116-0 / 3031941160 |
| ISBN-13 | 978-3-031-94116-0 / 9783031941160 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
