Artificial Intelligence-Enabled RF and Optical Communication Networks

Emerging Trends in 5G/6G and Internet of Things
1. Auflage 2027
ISBN: 978-1-041-34290-8
Verlag: Taylor & Francis Ltd

Buch, Englisch, 368 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Intelligent Radio Frequency and Optical Communication Technologies

The text explores the role of artificial intelligence in converging RF and optical technologies for 5G/6G and IoT. It addresses emergent challenges such as quantum security, intelligent spectrum sharing and hybrid FSO-RF resilience.

- Covers machine learning and deep learning techniques for enhancing spectrum efficiency, latency reduction, and adaptive beamforming in converged RF and free-space optical networks.

- Explores Artificial Intelligence-based massive MIMO, reconfigurable intelligent surfaces, and dynamic beam alignment for next-generation wireless networks.

- Discusses federated learning, edge computing, and lightweight artificial intelligence models for resource-constrained Internet of Things devices in RF-optical hybrid networks.

- Addresses generative adversarial networks (GANs) for channel prediction, physical-layer security, and adversarial attack mitigation in intelligent communication systems.

- Presents reinforcement learning (RL) and graph neural networks (GNNs) for real-time resource management, QoS optimization, and network slicing in 5G/6G ecosystems.

The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, optical communication, RF, wireless communication, telecommunication, and communication system design.

Zielgruppe

Academic, Postgraduate, and Undergraduate Advanced

Autoren/Hrsg.

Bhambri, Pankaj

Anand, A. Jose

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik

Inhaltsverzeichnis

Part 1: Foundations of Artificial Intelligence-Driven RF and Optical Communications. 1. Intelligent RF and Optical Networks: Evolution and Future Trajectories. 2. Fundamentals of Artificial Intelligence and Machine Learning for Wireless Communications. 3. Channel Modeling and Optimization in Artificial Intelligence-Enabled Hybrid RF-FSO Systems. Part 2: Artificial Intelligence for 5G/6G and IoT Convergence. 4. Artificial Intelligence-based Beamforming and MIMO Systems for 5G/6G. 5. Reinforcement Learning for Dynamic Spectrum Access in Internet of Things Networks. 6. Edge Intelligence and Federated Learning for Distributed RF-Optical Systems. Part 3: Emerging Applications and Case Studies. 7. Artificial Intelligence-Optimised Free-Space Optical (FSO) Links for Urban and Rural Connectivity. 8. Artificial Intelligence-Optimized Transceiver Design for Hybrid RF-FSO Systems. 9. Cognitive Radio Networks: AI-Driven Spectrum Sensing and Management. 10. Security and Privacy in Artificial Intelligence-Enabled Wireless Networks. 11. Global Regulatory Policies for Artificial Intelligence-RF Integration. Part 4: Challenges and Future Directions. 12. Artificial Intelligence for Energy-Efficient Green Communication Networks. 13. Case Studies: Real-World Deployments of Artificial Intelligence in RF and Optical Networks. 14. Beyond 6G: Quantum Machine Learning, Quantum Networking, and Terahertz Communications.

Über Autor(innen)

Dr. Pankaj Bhambri is an Associate Professor and Convener of the Board of Studies in the Department of Information Technology at Guru Nanak Dev Engineering College, Ludhiana, India. Recognized among the Top 2% of Scientists globally by Stanford University and Elsevier (2025), he has over twenty-one years of teaching and research experience. He earned his Ph.D. in Computer Science and Engineering from I.K.G. Punjab Technical University, Jalandhar. He is currently pursuing a Post Doctorate Fellowship from Lincoln University College, Malaysia. His research interests span machine learning, bioinformatics, cloud computing, and IoT. Dr. Bhambri has an extensive publication record, with numerous papers in high-impact SCIE and Scopus-indexed journals. He is a prolific author and editor, having contributed to and edited over two dozen books with prestigious publishers like Springer, CRC Press (Taylor & Francis), Elsevier, and IGI Global. He serves as a reviewer and technical committee member for numerous international conferences. Dr. Bhambri has also filed several patents, including an Australian innovation patent. He actively guides multiple Ph.D. scholars in cutting-edge areas of computer science and engineering.

Dr. A. Jose Anand is a Professor at the Department of Electronics and Communication Engineering, KCG College of Technology, Chennai, India. He has one year of industrial experience and over 25 years of teaching experience. He has presented several papers in prominent conferences, and has published several articles in reputed journal, and also published books in professional & engineering subjects. He is a member of Institution of Engineers, Computer Society of India, Institution of Engineering and Technology, Indian Society for Technical Education, etc. His current research interests include Wireless Sensor Networks, Embedded systems, IoT, Machine Learning and Image Processing, etc.