Dusit Niyato – författare

This unified treatment of game theory focuses on finding state-of-the-art solutions to issues surrounding the next generation of wireless and communications networks. Future networks will rely on autonomous and distributed architectures to improve the efficiency and flexibility of mobile applications, and game theory provides the ideal framework for designing efficient and robust distributed algorithms. This book enables readers to develop a solid understanding of game theory, its applications and its use as an effective tool for addressing wireless communication and networking problems. The key results and tools of game theory are covered, as are various real-world technologies including 3G networks, wireless LANs, sensor networks, dynamic spectrum access and cognitive networks. The book also covers a wide range of techniques for modeling, designing and analysing communication networks using game theory, as well as state-of-the-art distributed design techniques. This is an ideal resource for communications engineers, researchers, and graduate and undergraduate students.

Are you involved in designing the next generation of wireless networks? With spectrum becoming an ever scarcer resource, it is critical that new systems utilize all available frequency bands as efficiently as possible. The revolutionary technology presented in this book will be at the cutting edge of future wireless communications. Dynamic Spectrum Access and Management in Cognitive Radio Networks provides you with an all-inclusive introduction to this emerging technology, outlining the fundamentals of cognitive radio-based wireless communication and networking, spectrum sharing models, and the requirements for dynamic spectrum access. In addition to the different techniques and their applications in designing dynamic spectrum access methods, you'll also find state-of-the-art dynamic spectrum access schemes, including classifications of the different schemes and the technical details of each scheme. This is a perfect introduction for graduate students and researchers, as well as a useful self-study guide for practitioners.

Covering the fundamental theory together with the state of the art in research and development, this practical guide provides the techniques needed to design, analyze, and optimize device-to-device (D2D) communications in wireless networking. With an ever-increasing demand for higher data rate wireless access, D2D communication is set to become a key feature supported by next generation cellular networks. This book introduces D2D-based wireless communications from the physical, MAC, network, and application layer perspectives, providing all the key background information before moving on to discuss real-world applications as well as potential future developments. Key topics are discussed in detail, such as dynamic resource sharing (for example of spectrum and power) between cellular and ad hoc D2D communications to accommodate larger volumes of traffic and provide better service to users. Readers will understand the practical challenges of resource management, optimization, security, standardization, and network topology, and learn how the design principles are applied in practice.

Learn the fundamentals of architecture design, protocol optimization, and application development for wireless-powered communication networks with this authoritative guide. Readers will gain a detailed understanding of the issues surrounding architecture and protocol design, with key topics covered including relay-based energy harvesting systems, multiple-antenna systems for simultaneous wireless information and power transfer (SWIPT), performance modeling and analysis, and ambient wireless energy harvesting based cellular systems. Current applications of energy harvesting and transfer in different wireless networking scenarios are discussed, aiding the understanding of practical system development and implementation issues from an engineering perspective. The first book to provide a unified view of energy harvesting and wireless power transfer networks from a communications perspective, this is an essential text for researchers working on wireless communication networks and wireless systems, RF engineers, and wireless application developers.

Discover the very latest game-theoretic approaches for designing, modeling, and optimizing emerging wireless communication networks and systems with this unique text. Providing a unified and comprehensive treatment throughout, it explains basic concepts and theories for designing novel distributed wireless networking mechanisms, describes emerging game-theoretic tools from an engineering perspective, and provides an extensive overview of recent applications. A wealth of new tools is covered - including matching theory and games with bounded rationality - and tutorial chapters show how to use these tools to solve current and future wireless networking problems in areas such as 5G networks, network virtualization, software defined networks, cloud computing, the Internet of Things, context-aware networks, green communications, and security. This is an ideal resource for telecommunications engineers, and researchers in industry and academia who are working on the design of efficient, scalable, and robust communication protocols for future wireless networks, as well as graduate students in these fields.

Understand the fundamental principles and applications of ambient backscatter technology with this authoritative review. Covering both theory and practical engineering, leading researchers describe and explain hardware design, network design, and signal processing, and discuss architectures, protocols, communication methods, open research issues, emerging applications, and advanced system models with innovative solutions. This is an essential tool for graduate students, researchers, engineers, developers, and entrepreneurs.

Providing an extensive overview of the radio resource management problem in femtocell networks, this invaluable book considers both code division multiple access femtocells and orthogonal frequency-division multiple access femtocells. In addition to incorporating current research on this topic, the book also covers technical challenges in femtocell deployment, provides readers with a variety of approaches to resource allocation and a comparison of their effectiveness, explains how to model various networks using Stochastic geometry and shot noise theory, and much more.

Deep Reinforcement Learning for Wireless Communications and Networking Comprehensive guide to Deep Reinforcement Learning (DRL) as applied to wireless communication systems Deep Reinforcement Learning for Wireless Communications and Networking presents an overview of the development of DRL while providing fundamental knowledge about theories, formulation, design, learning models, algorithms and implementation of DRL together with a particular case study to practice. The book also covers diverse applications of DRL to address various problems in wireless networks, such as caching, offloading, resource sharing, and security. The authors discuss open issues by introducing some advanced DRL approaches to address emerging issues in wireless communications and networking. Covering new advanced models of DRL, e.g., deep dueling architecture and generative adversarial networks, as well as emerging problems considered in wireless networks, e.g., ambient backscatter communication, intelligent reflecting surfaces and edge intelligence, this is the first comprehensive book studying applications of DRL for wireless networks that presents the state-of-the-art research in architecture, protocol, and application design. Deep Reinforcement Learning for Wireless Communications and Networking covers specific topics such as: Deep reinforcement learning models, covering deep learning, deep reinforcement learning, and models of deep reinforcement learningPhysical layer applications covering signal detection, decoding, and beamforming, power and rate control, and physical-layer securityMedium access control (MAC) layer applications, covering resource allocation, channel access, and user/cell associationNetwork layer applications, covering traffic routing, network classification, and network slicingWith comprehensive coverage of an exciting and noteworthy new technology, Deep Reinforcement Learning for Wireless Communications and Networking is an essential learning resource for researchers and communications engineers, along with developers and entrepreneurs in autonomous systems, who wish to harness this technology in practical applications.

The book offers a succinct overview of the technical components of blockchain networks, also known as distributed digital ledger networks. Written from an academic perspective, it surveys ongoing research challenges as well as existing literature. Several chapters illustrate how the mathematical tools of game theory and algorithmic mechanism design can be applied to the analysis, design, and improvement of blockchain network protocols. Using an engineering perspective, insights are provided into how the economic interests of different types of participants shape the behaviors of blockchain systems. Readers are thus provided with a paradigm for developing blockchain consensus protocols and distributed economic mechanisms that regulate the interactions of system participants, thus leading to desired cooperative behaviors in the form of system equilibria. This book will be a vital resource for students and scholars of this budding field.

Metaverse Communication and Computing Networks Understand the future of the Internet with this wide-ranging analysis “Metaverse” is the term for applications that allow users to assume digital avatars to interact with other humans and software functions in a three-dimensional virtual space. These applications and the spaces they create constitute an exciting and challenging new frontier in digital communication. Surmounting the technological and conceptual barriers to creating the Metaverse will require researchers and engineers familiar with its underlying theories and a wide range of technologies and techniques. Metaverse Communication and Computing Networks provides a comprehensive treatment of Metaverse theory and the technologies that can be brought to bear on this new pursuit. It begins by describing the Metaverse’s underlying architecture and infrastructure, physical and digital, before addressing how existing technologies are being adapted to its use. It concludes with an overview of the challenges facing the Metaverse. The result is a thorough introduction to a subject that may define the future of the internet. Metaverse Communication and Computing Networks readers will also find: Detailed treatment of technologies, including artificial intelligence, Virtual Reality, Extended Reality, and moreAnalysis of issues including data security, ethics, privacy, and social impactA real-world prototype for Metaverse applicationsMetaverse Communication and Computing Networks is a must-own for researchers and engineers looking to understand this growing area of technology, and entrepreneurs interested in establishing Metaverse businesses.

A guide to the challenges in making virtual reality, reality The Metaverse, a version of the internet in which online interactions take place in real time within fully realized virtual spaces, has been promised as the next frontier in wireless communication. It has drawn huge investment from Silicon Valley and widespread media attention. However, the technologies required to make the Metaverse a reality are still in their infancy, and significant barriers must be overcome if this massive step is to be taken. Realizing the Metaverse provides a systematic overview of these challenges and their likely solutions. Focusing on five key areas—infrastructure, access, intelligence, security, and future developments—it offers one of the first comprehensive, formalized treatments of the Metaverse as a nascent reality. It promises to be an integral contribution to the future development of Metaverse technologies. Realizing the Metaverse readers will also find: An editorial team with extensive research experience in the fieldDetailed discussion of topics such as augmented reality (AR) adaptation, haptic feedback, artificial intelligence, and moreEnlightening discussion of open questions and future prospects for researchRealizing the Metaverse is ideal for graduate and advanced undergraduate students in wireless technology, network communications, and related fields, as well as for researchers and industry professionals involved with the Metaverse or adjacent technologies.

Understand the cutting-edge technology of semantic communications and its growing applications Semantic communications constitute a revolution in wireless technology, combining semantic theory with wireless communication. In a semantic communication, essential information is encoded at the source, drastically reducing the required data usage, and then decoded at the destination in such a way that all key information is recovered, even if transmission is damaged or incomplete. Enhancing the correspondence between background knowledge at source and destination can drive the data usage requirement even lower, producing ultra-efficient information exchanges with ultra-low semantic ambiguity. Wireless Semantic Communications offers a comprehensive overview of this groundbreaking field, its development, and its future application. Beginning with an introduction to semantic communications and its foundational principles, the book then proceeds to cover transceiver design and methods, before discussing use cases and future developments. The result is an indispensable resource for understanding the future of wireless communication. Readers will also find: Analysis of transceiver optimization methods and resource management for semantic communicationDetailed discussion of topics including semantic encoding and decoding, Shannon information theory, and many moreA team of editors with decades of combined experience in the study of wireless communicationsWireless Semantic Communications is ideal for electrical and computing engineers and researchers, as well as industry professionals working in wireless communications.

Comprehensive review of state-of-the-art research and development in Generative AI for future communications and networking Generative AI for Communications Systems provides a systematic foundation of knowledge on Generative AI for communications and networking. This book discusses the great potential and challenges in applying Generative AI as promising solutions to future communications systems and enables and facilitates “Generative AI as a Service” by exploring novel communications, networking architectures, protocols, and research trends. The book also includes information on: Crucial challenges to solve in Generative AI, such as training data availability, computational complexity, generalization for various scenarios, robustness of noisy and incomplete data, and real-time adaptation in communications and networking systemsCybersecurity concerns such as ethics and privacy in relation to Generative AIApplications of Generative AI across various layers, including the PHY layer, MAC layer, Network layer, and Application layerCommunications and networking solutions to meet the computing and communications challenges and demands to train and deploy large-scale Generative AI modelsGenerative AI for Communications Systems is an excellent up-to-date resource on the subject for scholars and researchers in the fields of communications, artificial intelligence, machine learning, and network optimization as well as professionals working in the communications industry including engineers, network architects, and system designers.

This book constitutes the refereed proceedings of the 13th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2021, held in Phuket, Thailand, in April 2021.*The 67 full papers accepted for publication in these proceedings were carefully reviewed and selected from 291 submissions.

This book first presents a tutorial on Federated Learning (FL) and its role in enabling Edge Intelligence over wireless edge networks.

This book first presents a tutorial on Federated Learning (FL) and its role in enabling Edge Intelligence over wireless edge networks. This provides readers with a concise introduction to the challenges and state-of-the-art approaches towards implementing FL over the wireless edge network. Then, in consideration of resource heterogeneity at the network edge, the authors provide multifaceted solutions at the intersection of network economics, game theory, and machine learning towards improving the efficiency of resource allocation for FL over the wireless edge networks. A clear understanding of such issues and the presented theoretical studies will serve to guide practitioners and researchers in implementing resource-efficient FL systems and solving the open issues in FL respectively.

This book examines whether the integration of edge intelligence (EI) and blockchain (BC) can open up new horizons for providing ubiquitous intelligent services. Accordingly, the authors conduct a summarization of the recent research efforts on the existing works for EI and BC, further painting a comprehensive picture of the limitation of EI and why BC could benefit EI. To examine how to integrate EI and BC, the authors discuss the BC-driven EI and tailoring BC to EI, including an overview, motivations, and integrated frameworks. Finally, some challenges and future directions are explored. The book explores the technologies associated with the integrated system between EI and BC, and further bridges the gap between immature BC and EI-amicable BC.Explores the integration of edge intelligence (EI) and blockchain (BC), including their integrated motivations, frameworks and challenges;Presents how BC-driven EI can realize computing-power management, data administration, and model optimization;Describes how to tailor BC to better support EI, including flexible consensus protocol, effective incentive mechanism, intellectuality smart contract, and scalable BC system tailoring;Presents some key research challenges and future directions for the integrated system.

This book examines whether the integration of edge intelligence (EI) and blockchain (BC) can open up new horizons for providing ubiquitous intelligent services. Accordingly, the authors conduct a summarization of the recent research efforts on the existing works for EI and BC, further painting a comprehensive picture of the limitation of EI and why BC could benefit EI. To examine how to integrate EI and BC, the authors discuss the BC-driven EI and tailoring BC to EI, including an overview, motivations, and integrated frameworks. Finally, some challenges and future directions are explored. The book explores the technologies associated with the integrated system between EI and BC, and further bridges the gap between immature BC and EI-amicable BC.Explores the integration of edge intelligence (EI) and blockchain (BC), including their integrated motivations, frameworks and challenges;Presents how BC-driven EI can realize computing-power management, data administration, and model optimization;Describes how to tailor BC to better support EI, including flexible consensus protocol, effective incentive mechanism, intellectuality smart contract, and scalable BC system tailoring;Presents some key research challenges and future directions for the integrated system.

This book provides a comprehensive exploration of stochastic processes and their critical applications in enhancing physical layer security for modern communication systems. The book uniquely focuses on the intersection of advanced mathematical models and cutting-edge security techniques, making complex concepts accessible and practical for real-world applications. The book first presents a comprehensive theoretical study of stochastic processes and their applications in physical layer security. Guided by these theoretical foundations, the authors then offer practical design strategies to enhance the performance of communication systems and facilitate their implementation. The book equips researchers, engineers, and security professionals with the knowledge and tools to tackle contemporary challenges. By bridging the gap between theory and practice, the authors ensure that readers can implement effective security measures in the ever-evolving landscape of modern communications.Comprehensively covers physical layer security, offering cutting-edge strategies beyond traditional encryption methods;Combines principles from probability theory, information theory, and communication systems for a comprehensive view;Provides design strategies based on theoretical foundations, making it easier deploy secure communication systems.

This book explores the integration and interplay of model-based optimization and model-free deep reinforcement learning (DRL).  It addresses the growing complexity of future wireless networks. This book begins with a concise overview of foundational DRL algorithms and then delves into advanced frameworks, including optimization-driven DRL, hierarchical DRL, multi-agent DRL, Bayesian-enhanced DRL, and Lyapunov-guided DRL. Each framework is illustrated through case studies in emerging scenarios such as intelligent reflecting surface (IRS)-assisted wireless communications, UAV-assisted wireless networks, backscatter-assisted relay communications, and mobile edge computing.Each chapter of this book demonstrates how partial system knowledge, inherent structural properties, and problem decomposition can dramatically accelerate learning convergence. It also improves sample efficiency, and enhance robustness in decentralized, dynamic, and large-scale wireless networks.Tailored for researchers and graduate students focused on wireless communications and AI-driven networking, it bridges theoretical innovation with practical implementation challenges.  It provides a roadmap for designing intelligent, autonomous, and resource-efficient next-generation wireless systems. Engineers and professional specializing in AI and machine learning for wireless systems will also find this book useful as a reference.

By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial.

By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial.

This book investigates the resource allocation in backscatter-assisted communication networks. With the development of backscatter communications, integrating backscatter communication technology into traditional communication networks can improve the network performance significantly. To fully improve the performance of backscatter-assisted communication networks, resource allocation is of special importance. It is worth to mention that the resource allocation in backscatter-assisted communication networks is more challenging than that in traditional communication networks, and the tradeoff of the performance between backscatter communications and traditional communications needs to be carefully considered. In this book, considering that game theory is an attractive tool for developing and analyzing distributed, flexible, and autonomous networks, we develop the auction-based time scheduling schemes, contract-based time assignment scheme, and evolutionary game-based access point and service selection scheme for the backscatter-assisted radio-frequency-powered cognitive networks, where some important properties such as individual rationality are considered. We also employ the optimization approach and develop a relay mode selection and resource sharing scheme for backscatter-assisted hybrid relay networks to improve the throughput. We believe that the developed resource allocation schemes in this book can provide useful guidance for the design of backscatter-assisted communication networks and future Internet of Things. Graduate students, researchers, and engineers in the field of communication networks can benefit from the book.

This book establishes game-theoretical frameworks based on the mechanism design theory and proposes strategy-proof algorithms, to optimally allocate and price the related IoT services, so that the social welfare of IoT ecosystem or the service provider’s revenue can be maximized and the IoT service provision can be sustainable.