AI for Large Scale Communication Networks


Book Description

Artificial Intelligence (AI) is rapidly becoming essential to large-scale communication networks. Driven by the need for greater efficiency, security, and optimization, AI has evolved into a powerful tool that processes vast data and delivers insights through real-time processing, predictive analysis, and adaptive learning. Because these advancements transform how we interact with data and services, applying AI to complex networks has never been more essential. AI for Large Scale Communication Networks explores how AI can enhance network performance, scalability, and security. With contributions from experts, this book covers topics such as algorithm optimization, machine learning improvements, and neural network applications. It also addresses critical challenges like fault tolerance and distributed computing, emphasizing the need for interdisciplinary collaboration. Designed for academics, practitioners, and students, this resource provides actionable insights and strategies to optimize communication networks using AI.




Artificial Intelligence and Quantum Computing for Advanced Wireless Networks


Book Description

ARTIFICIAL INTELLIGENCE AND QUANTUM COMPUTING FOR ADVANCED WIRELESS NETWORKS A comprehensive presentation of the implementation of artificial intelligence and quantum computing technology in large-scale communication networks Increasingly dense and flexible wireless networks require the use of artificial intelligence (AI) for planning network deployment, optimization, and dynamic control. Machine learning algorithms are now often used to predict traffic and network state in order to reserve resources for smooth communication with high reliability and low latency. In Artificial Intelligence and Quantum Computing for Advanced Wireless Networks, the authors deliver a practical and timely review of AI-based learning algorithms, with several case studies in both Python and R. The book discusses the game-theory-based learning algorithms used in decision making, along with various specific applications in wireless networks, like channel, network state, and traffic prediction. Additional chapters include Fundamentals of ML, Artificial Neural Networks (NN), Explainable and Graph NN, Learning Equilibria and Games, AI Algorithms in Networks, Fundamentals of Quantum Communications, Quantum Channel, Information Theory and Error Correction, Quantum Optimization Theory, and Quantum Internet, to name a few. The authors offer readers an intuitive and accessible path from basic topics on machine learning through advanced concepts and techniques in quantum networks. Readers will benefit from: A thorough introduction to the fundamentals of machine learning algorithms, including linear and logistic regression, decision trees, random forests, bagging, boosting, and support vector machines An exploration of artificial neural networks, including multilayer neural networks, training and backpropagation, FIR architecture spatial-temporal representations, quantum ML, quantum information theory, fundamentals of quantum internet, and more Discussions of explainable neural networks and XAI Examinations of graph neural networks, including learning algorithms and linear and nonlinear GNNs in both classical and quantum computing technology Perfect for network engineers, researchers, and graduate and masters students in computer science and electrical engineering, Artificial Intelligence and Quantum Computing for Advanced Wireless Networks is also an indispensable resource for IT support staff, along with policymakers and regulators who work in technology.




Computing in Communication Networks


Book Description

Computing in Communication Networks: From Theory to Practice provides comprehensive details and practical implementation tactics on the novel concepts and enabling technologies at the core of the paradigm shift from store and forward (dumb) to compute and forward (intelligent) in future communication networks and systems. The book explains how to create virtualized large scale testbeds using well-established open source software, such as Mininet and Docker. It shows how and where to place disruptive techniques, such as machine learning, compressed sensing, or network coding in a newly built testbed. In addition, it presents a comprehensive overview of current standardization activities. Specific chapters explore upcoming communication networks that support verticals in transportation, industry, construction, agriculture, health care and energy grids, underlying concepts, such as network slicing and mobile edge cloud, enabling technologies, such as SDN/NFV/ ICN, disruptive innovations, such as network coding, compressed sensing and machine learning, how to build a virtualized network infrastructure testbed on one's own computer, and more. - Provides a uniquely comprehensive overview on the individual building blocks that comprise the concept of computing in future networks - Gives practical hands-on activities to bridge theory and implementation - Includes software and examples that are not only employed throughout the book, but also hosted on a dedicated website




Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning


Book Description

COMMUNICATION NETWORKS AND SERVICE MANAGEMENT IN THE ERA OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Discover the impact that new technologies are having on communication systems with this up-to-date and one-stop resource Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more. The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligence An exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based management, and network virtualization-based management Discussions of AI and ML for architectures and frameworks, including cloud systems, software defined networks, 5G and 6G networks, and Edge/Fog networks An examination of AI and ML for service management, including the automatic generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management.




AI and Its Convergence With Communication Technologies


Book Description

The integration of Artificial Intelligence (AI) with Communication Technologies (ICT) is a critical aspect of research and development today, but it poses numerous challenges and bottlenecks. To address these issues, the book AI and Its Convergence with Communication Technologies, edited by a team of expert scholars, provides a comprehensive overview of the state-of-the-art research and practical challenges related to AI's convergence with ICT. It is designed to benefit engineers, professionals, scientists, and academicians, providing them with insights into the ICT industry and research from an AI perspective. The book covers a wide range of topics, including recent advancements and applications in AI, AI in signal processing, AI in mobile and modern wireless networks, and AI towards automation. It also addresses potential applications of AI in national defense, military technology, hybrid warfare, medical and health sciences, and energy-efficient systems. Furthermore, the book highlights the strengths and weaknesses of AI convergence with ICT, along with emerging frontiers and recommendations. It provides a brief history of AI in ICT and a comprehensive introduction to ICT-related methods and techniques in artificial intelligence and machine learning. The book emphasizes the role of AI in extracting knowledge and making predictions in decision-making strategies for businesses, management, and governance. Overall, this book offers a significant contribution to the understanding of AI and its convergence with communication technologies, making it a must-read for scholars and researchers who seek to understand the intersection of AI and ICT and how it impacts modern industries and research.




6G Wireless Communications and Mobile Networking


Book Description

6G Wireless Communications and Mobile Networking introduces the key technologies behind 6G wireless communication and mobile networking to the reader. The book starts with a general vision of 6G technology, which includes the motivation that drives 6G research, the international organizations working on 6G standardization and recent progress in 6G research. Separate chapters on millimeter-wave and terahertz-wave technologies in 6G, the development of latest 6G antenna technology as well as related wireless communication applications are included in the contents. The book also provides details about the 6G network layer, such as self-organizing network driven by network slicing, software-defined networking and network function virtualization. Finally, it covers some popular research topics, including the challenges and solutions to massive 6G IoT networks, 6G cloud/edge computing and big data systems that may appear in the foreseeable future. Key Features: - Provides a complete introduction to 6G vision and technology - Consists of both basic theories and frontier technologies - Separate chapters on key topics such as 6G physical layers, millimeter wave and terahertz technology and advanced antenna arrays - Covers future trends and applications such as intelligent management systems, 6G IoT networks, cloud/edge computing and big data applications This focused reference will significantly enhance the knowledge of engineering students and apprentices involved in the field of telecommunications. Readers interested in cutting-edge wireless networking technologies will also benefit from the information provided.




6G Communication Network


Book Description

This book focuses on 6G technology beyond 5G. The objective of next generation 6G wireless communications is to improve the benchmarks while simultaneously delivering additional services. Many widely expected future services, such as life‐critical services and wireless brain‐computer interactions, will be important to their success. This book presents the evolution of 6G technology, architecture, and implementation. This book provides a comprehensive overview of the theoretical and experimental modelling of 6G communication, providing detailed implementation issues and performance evaluation of emerging technologies along with research results, and networking methods. This book: • Contains a comprehensive overview of 6G communication network technology. • Contains both fundamental theories and cutting‐edge technologies. • Covers implementations, architecture, security, privacy, and reliability in 6G communication and performance analysis of the 6G communication. • Future trends and applications covered include vehicle‐to‐everything, massive radio access networks, Massive IoT Access Cybertwin, Sustainable Society 5.0 using 6G communication. • Covers the challenges and research directions to enable future research to make 6G communication a wireless solution for sustainability. • Contains a comprehensive overview of 6G communication network technology. • Contains both fundamental theories and cutting‐edge technologies. • Covers implementations, architecture, security, privacy, and reliability in 6G communication and performance analysis of the 6G communication. • Future trends and applications covered include vehicle‐to‐everything, massive radio access networks, Massive IoT Access Cybertwin, Sustainable Society 5.0 using 6G communication. • Covers the challenges and research directions to enable future research to make 6G communication a wireless solution for sustainability. This book is primarily written for senior undergraduate students, graduate students, and academic researchers in the fields of electrical engineering, electronics, communications engineering, and computer science and engineering.







Implementing Data Analytics and Architectures for Next Generation Wireless Communications


Book Description

Wireless communication is continuously evolving to improve and be a part of our daily communication. This leads to improved quality of services and applications supported by networking technologies. We are now able to use LTE, LTE-Advanced, and other emerging technologies due to the enormous efforts that are made to improve the quality of service in cellular networks. As the future of networking is uncertain, the use of deep learning and big data analytics is a point of focus as it can work in many capacities at a variety of levels for wireless communications. Implementing Data Analytics and Architectures for Next Generation Wireless Communications addresses the existing and emerging theoretical and practical challenges in the design, development, and implementation of big data algorithms, protocols, architectures, and applications for next generation wireless communications and their applications in smart cities. The chapters of this book bring together academics and industrial practitioners to exchange, discuss, and implement the latest innovations and applications of data analytics in advanced networks. Specific topics covered include key encryption techniques, smart home appliances, fog communication networks, and security in the internet of things. This book is valuable for technologists, data analysts, networking experts, practitioners, researchers, academicians, and students.




Multi-Hierarchical Representation of Large-Scale Space


Book Description

It has been stated in psychology that human brain arranges information in a way that improves efficiency in performing common tasks, for example, information about our spatial environment is conveniently structured for efficient route finding. On the other hand, in computational sciences, the use of hierarchical information is well known for reducing the complexity of solving problems. This book studies hierarchical representations of large-scale space and presents a new model, called Multi-AH-graph, that uses multiple hierarchies of abstraction. It allows an agent to represent structural information acquired from the environment (elements such as objects, free space, etc., relations existing between them, such as proximity, similarity, etc. and other types of information, such as colors, shapes, etc). The Multi-AH-graph model extends a single hierarchy representation to a mUltiple hierarchy arrangement, which adapts better to a wider range of tasks, agents, and environments. We also present a system called CLAUDIA, which is an implementation of the task-driven paradigm for automatic construction of multiple abstractions: a set of hierarchies of abstraction will be "good" for an agent if it can reduce the cost of planning and performing certain tasks of the agent in the agent's world. CLAUDIA constructs multiple hierarchies (Multi-AH-graphs) for a given triple , trying to optimize their "goodness".