This book includes peer-reviewed papers from the 3rd International Conference on 6G Communications Networking and Signal Processing (SGCNSP) 2025. It provides a comprehensive overview of the emerging field of 6G communications, covering key networking concepts, signal processing techniques, and future applications. The book introduces the evolution of cellular networks and the fundamental features of 6G, highlighting the challenges and opportunities in its development. It serves as a valuable reference for academics, engineers, and industry professionals seeking to understand the latest…mehr
This book includes peer-reviewed papers from the 3rd International Conference on 6G Communications Networking and Signal Processing (SGCNSP) 2025. It provides a comprehensive overview of the emerging field of 6G communications, covering key networking concepts, signal processing techniques, and future applications. The book introduces the evolution of cellular networks and the fundamental features of 6G, highlighting the challenges and opportunities in its development. It serves as a valuable reference for academics, engineers, and industry professionals seeking to understand the latest advancements and potential applications of 6G technology in the evolving landscape of telecommunications.
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Autorenporträt
Wong Kin Shun Terence received his B.A. and Ph.D. degrees in Electrical Engineering from Cambridge University in 1987 and 1992, respectively. He joined NTU in 1994 and is presently a tenured Associate Professor in the Microelectronics Division of the School of EEE. His research interests are mainly in organic electronics, silicon nano-electronic devices, characterization, and interconnects. His work has been supported by several research grants. He has published in leading international journals and is the author of one book chapter. His teaching profile includes advanced semiconductor devices and display Technologies. He is a Senior Member of the IEEE and a Chartered Physicist of the Institute of Physics. Since 2006, he has been a member of the Gerson Lehrman Technology Council, a consulting firm in Austin, Texas.
Vinod Kiran Kappala received his M.Tech. and Ph.D. in Communication and Networks from the National Institute of Technology Rourkela, India, in 2015 and 2022, respectively. He pursued his postdoctoral studies at the Indian Institute of Science (IISc), Bengaluru, India. Currently, he is working as an Assistant Professor in the School of Electronics Engineering (SENSE), VIT-AP University, Andhra Pradesh, India. His research interests include optical wireless communication, free space optics, optical networking, and embedded systems.
Inhaltsangabe
Mean value analysis approach with transmission opportunity for IEEE 802.11ah basedNOMA-IoT Network.- Design of Fractal Patch antenna for Wireless Applications.- Evaluating the Use of Cone Beam Computed Tomography in Diagnosing Dental Conditions.- Enhancing the Precision of Drug Interaction Alerts in Clinical Decision Support Systems Through Deep Learning Techniques.- Performance Analysis of Computational Models for Identifying High-Risk Prescriptions in Geriatric Patients.- Development and Performance Evaluation of Machine Learning Algorithms for Predicting Pharmacokinetics in Rare Diseases.- Blockchain-Enabled Medication Tracking: Enhancing Patient Safety in Clinical Pharmacy.- Leveraging Pharmacogenomics for Precision Medicine: A Blockchain Approach to Secure Data Sharing.- Machine Learning Algorithms for Real-Time Drug Interaction Predictions in Clinical Settings.- AI-Driven Video Translation to Indian Languages: A Multilingual Perspective.- Detection and Estimation of Signal Processing in MIMO Systems using Sparse Bayesian Learning.
Mean value analysis approach with transmission opportunity for IEEE 802.11ah basedNOMA-IoT Network.- Design of Fractal Patch antenna for Wireless Applications.- Evaluating the Use of Cone Beam Computed Tomography in Diagnosing Dental Conditions.- Enhancing the Precision of Drug Interaction Alerts in Clinical Decision Support Systems Through Deep Learning Techniques.- Performance Analysis of Computational Models for Identifying High-Risk Prescriptions in Geriatric Patients.- Development and Performance Evaluation of Machine Learning Algorithms for Predicting Pharmacokinetics in Rare Diseases.- Blockchain-Enabled Medication Tracking: Enhancing Patient Safety in Clinical Pharmacy.- Leveraging Pharmacogenomics for Precision Medicine: A Blockchain Approach to Secure Data Sharing.- Machine Learning Algorithms for Real-Time Drug Interaction Predictions in Clinical Settings.- AI-Driven Video Translation to Indian Languages: A Multilingual Perspective.- Detection and Estimation of Signal Processing in MIMO Systems using Sparse Bayesian Learning.
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