Ekram Hossain – författare

Heterogeneous wireless networking, which is sometimes referred to as the fourth-generation (4G) wireless, is a new frontier in the future wireless communications technology and there has been a growing interest on this topic among researchers and engineers in both academia and industry. This book will include a set of research and survey articles featuring the recent advances in theory and applications of heterogeneous wireless networking technology for the next generation (e.g., fourth generation) wireless communications systems. With the rapid growth in the number of wireless applications, services and devices, using a single wireless technology such as a second generation (2G) and third generation (3G) wireless system would not be efficient to deliver high speed data rate and quality-of-service (QoS) support to mobile users in a seamless way. Fourth generation (4G) wireless systems are devised with the vision of heterogeneity in which a mobile user/device will be able to connect to multiple wireless networks (e.g., WLAN, cellular, WMAN) simultaneously. This book intends to provide a unified view on the state-of-the-art of protocols and architectures for heterogeneous wireless networking. The contributed articles will cover both the theoretical concepts and system-level implementation issues related to design, analysis, and optimization of architectures and protocols for heterogeneous wireless access networks.

Introduction to Network Simulator NS2 is a primer providing materials for NS2 beginners, whether students, professors, or researchers for understanding the architecture of Network Simulator 2 (NS2) and for incorporating simulation modules into NS2. The authors discuss the simulation architecture and the key components of NS2 including simulation-related objects, network objects, packet-related objects, and helper objects.

The NS2 modules included within are nodes, links, SimpleLink objects, packets, agents, and applications. Further, the book covers three helper modules: timers, random number generators, and error models. Also included are chapters on summary of debugging, variable and packet tracing, result compilation, and examples for extending NS2. Two appendices provide the details of scripting language Tcl, OTcl and AWK, as well object oriented programming used extensively in NS2.

Introduction to Network Simulator NS2 can be used by researchers, professionals or graduate students studying telecommunication networks.

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:

With 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.

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:

With 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.

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:

Metaverse 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.