Advances in Underwater Communication and Networking
Produktdetaljer
Biografisk notat
Syed Ali Hassan serves as a professor at the National University of Sciences and Technology (NUST), Pakistan, where he directs the Information Processing and Transmission Laboratory. His research primarily addresses theoretical aspects of wireless communications, with over 300 published articles in this filed. He obtained a PhD in electrical engineering from Georgia Institute of Technology, United States. Huma Ghafoor holds the position of assistant professor at the School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Pakistan. Until January 2019, she worked as a postdoctoral researcher at Inha University, South Korea. Her research interests include vehicular ad hoc networks, maritime networks, and underwater sensor networks. She completed her PhD in electrical engineering from the University of Ulsan, South Korea, in 2018.Underwater communication systems have been gaining significant interest over the past two decades in addressing various applications, ranging from the depths of the ocean to its surface. To implement applications such as oil monitoring, earthquake and tsunami detection, marine animal study and military surveillance, underwater communications are crucial in establishing reliable connections between sensor nodes.
Advances in Underwater Communication and Networking covers 6G-based underwater acoustic communications that integrate modern technologies such as software-defined networking (SDN), network function virtualization (NFV), non-orthogonal multiple access (NOMA), reconfigurable intelligent surfaces (RIS), unmanned aerial vehicles (UAVs), autonomous underwater vehicles (AUVs), and AI.
The book investigates NOMA as a solution to enhance spectral efficiency and user fairness in order to tackle acoustic band issues. This is followed by a detailed exploration of various machine learning and deep learning techniques for exploring underwater acoustic environments, optimizing acoustic signal transmission, and using hybrid intelligent models to power acoustic communications. The later chapters explore those few underwater applications that cover AI-based seismic monitoring, detection of tsunamis and earthquakes using AI-based models, and AI-based sonar image classification and analysis. In the final two chapters, the focus is on testing sound propagation in water and using various sonar systems to acquire underwater images and investigate real-life applications such as mine-detection, seabed mapping, and AUV navigation. Finally, a modelling scenario is developed and verified using the UPPAAL model checker for sonar-based subsystems.
Advances in Underwater Communication and Networking discusses a variety of recent concepts that will open new avenues for researchers in this field to explore underwater environments using 6G concepts and technologies.
The book describes recent technologies that can be integrated to overcome existing issues in sonar communication and sensing networks. It is aimed at researchers in the field of sonar communications and networking, and those interested in exploring hybrid communications among maritime and underwater networks.
- Chapter 1: The 6G internet of underwater things (6G-IoUT)
- Chapter 2: Software-defined underwater acoustic communication
- Chapter 3: Exploring the TCP/IP protocol stack in underwater networks: adapting to SDN-based 6G underwater networks
- Chapter 4: Integrating SDN and NFV to deploy early warning systems in marine distributed underwater networks (MDUN)
- Chapter 5: NOMA-based underwater acoustic communication
- Chapter 6: Reconfigurable intelligent surfaces in challenging underwater environment
- Chapter 7: Routing strategies for 6G underwater communication networks
- Chapter 8: Energy-efficient routing protocols in underwater acoustic networks
- Chapter 9: Impact of the provision of constrained energy on UAV-enabled 6G underwater networks
- Chapter 10: Optimizing UAV battery usage for supporting underwater acoustic networks
- Chapter 11: Crypto-secure UASN: secure communication for the network layer of underwater acoustic sensor networks
- Chapter 12: Secure underwater acoustic communication using 6G technologies
- Chapter 13: AI for securing data integrity in acoustic communication links
- Chapter 14: Underwater acoustic communications powered by machine learning
- Chapter 15: Machine learning techniques for optimizing underwater acoustic signal transmission
- Chapter 16: Exploring the underwater acoustic environment through deep learning
- Chapter 17: Deep learning techniques for optimizing underwater acoustic communication
- Chapter 18: Underwater acoustic communications powered by hybrid intelligent models
- Chapter 19: AI-based seismic monitoring using underwater acoustic sensing
- Chapter 20: Detection of tsunamis and earthquakes through underwater sensor networks
- Chapter 21: Underwater SONAR image classification and analysis with the aid of AI
- Chapter 22: Intelligent evaluation and categorization nof SONAR images
- Chapter 23: Real-time modeling and verification of SONAR systems