Explainable AI for Communications and Networking: Toward Responsible Automation gives a tour into the realm of Explainable Artificial Intelligence (XAI) and its impact on transparent and autonomous communication networks. The book equips readers from diverse backgrounds in communications and networking with a variety of XAI tools, metrics and frameworks to demystify AI systems through graphical taxonomies and mathematical formulations, which are further enriched with code snippets. The book also examines XAI implementation in wireless communications, network management, generative AI for telecom and cybersecurity, before presenting practical use-cases emanating from an industry perspective. Finally, the regulatory, ethical, and legal implications of XAI in telecommunications are reviewed, before concluding with key challenges and takeaways.
Open Radio Access Network (O-RAN) Systems Architecture and Design, Second Edition provides a jumpstart to engineers developing O-RAN hardware and software systems, presenting a top-down approach to O-RAN systems design. It gives an introduction into why wireless systems look the way they do before introducing relevant O-RAN and 3GPP standards. The remainder of the book discusses hardware and software aspects of O-RAN system design, including dimensioning and performance targets.
The Core Network for 5G Advanced, Second Edition covers up to the 3GPP release 17 & 18 which includes the core network for 5G Advanced as well as a large number of new features added by 3GPP to expand the initial 5G Core specifications in rel-15/16. This new release includes A complete update to reflect developments in Releases 17 and 18, along with new chapters on Service Exposure, non-3GPP access, 3GPP access for new use cases, Edge computing, Industry and Enterprise features, Regulatory services and Network automation and AI/ML, an overview of the 5G Core Architecture, and much more.Examples of 5G network deployment options for different use cases are also included. Written by authors who are heavily involved in the development of 5G standards, and who have written several successful books on 4G and 5G Core Networks, this book provides an authoritative reference on the technologies and standards of the 3GPP 5G Core network.
Machine Learning for Low-Latency Communications presents the principles and practice of various deep learning methodologies for mitigating three critical latency components: access latency, transmission latency, and processing latency. In particular, the book develops learning to estimate methods via algorithm unrolling and multiarmed bandit for reducing access latency by enlarging the number of concurrent transmissions with the same pilot length. Task-oriented learning to compress methods based on information bottleneck are given to reduce the transmission latency via avoiding unnecessary data transmission.Lastly, three learning to optimize methods for processing latency reduction are given which leverage graph neural networks, multi-agent reinforcement learning, and domain knowledge. Low-latency communications attracts considerable attention from both academia and industry, given its potential to support various emerging applications such as industry automation, autonomous vehicles, augmented reality and telesurgery. Despite the great promise, achieving low-latency communications is critically challenging. Supporting massive connectivity incurs long access latency, while transmitting high-volume data leads to substantial transmission latency.
TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyML as applied to the Internet of Things (IoT) and low-power wide area networks (LPWANs). It starts by providing the foundations of IoT/LPWANs, low-power embedded systems and hardware, the role of AI and machine learning in communication networks in general, and cloud/edge intelligence. It then presents the concepts, methods, algorithms, and tools of TinyML. Practical applications of TinyML are given from the healthcare and industrial sectors, providing practical guidance on the design of applications and the selection of appropriate technologies.
Open Radio Access Network (O-RAN) Systems Architecture and Design gives a jump-start to engineers developing O-RAN hardware and software systems, providing a top-down approach to O-RAN systems design. It gives an introduction into why wireless systems look the way they do today before introducing relevant O-RAN and 3GPP standards. The remainder of the book discusses hardware and software aspects of O-RAN system design, including dimensioning and performance targets.
Orthogonal Frequency Division Multiplexing (OFDM) has been the waveform of choice for most wireless communications systems in the past 25 years. This book addresses the “what comes next?” question by presenting the recently proposed waveform known as Orthogonal Time-Frequency-Space (OTFS), which offers a better alternative for high-mobility environments. The OTFS waveform is based on the idea that the mobile wireless channels can be effectively modelled in the delay-Doppler domain. This domain provides a sparse representation closely resembling the physical geometry of the wireless channel. The key physical parameters such as relative velocity and distance of the reflectors with respect to the receiver can be considered roughly invariant in the duration of a frame up to a few milliseconds. This enables the information symbols encoded in the delay-Doppler domain to experience a flat fading channel even when they are affected by multiple Doppler shifts present in high-mobility environments. Delay-Doppler Communications: Principles and Applications covers the fundamental concepts and the underlying principles of delay-Doppler communications. Readers familiar with OFDM will be able to quickly understand the key differences in delay-Doppler domain waveforms that can overcome some of the challenges of high-mobility communications. For the broader readership with a basic knowledge of wireless communications principles, the book provides sufficient background to be self-contained. The book provides a general overview of future research directions and discusses a range of applications of delay-Doppler domain signal processing.
Intelligent Sensing and Communications for Internet of Everything introduces three application scenarios of enhanced mobile broadband (eMBB), large-scale machine connection (mMTC) and ultra reliable low latency communication (URLLC). A new communication model, namely backscatter communication (BackCom), intelligent reflector surface (IRS) and unmanned aerial vehicle (UAV) technology in Internet of Everything (IoE), is described in detail. Also focusing on millimeter wave, the book discusses the potential application of terahertz 6G network spectrum in the Internet of Things (IoT). Finally, the applications of IoE network in big data, artificial intelligence (AI) technology and fog/edge computing technology are proposed.
5G NR: The Next Generation Wireless Access Technology, Second Edition, follows the authors' highly celebrated books on 3G and 4G and provides a new level of insight into 5G NR. After background discussion of 5G, including requirements, spectrum aspects, and the standardization timeline, all technology features of the first phase of NR are described in detail. The book covers the NR physical-layer structure and higher-layer protocols, RF and spectrum aspects, and co-existence and interworking with LTE. The book provides a good foundation in NR and different NR technology components, giving insight into why a certain solution has been selected.This second edition is updated to reflect the latest developments in Release 16 and includes brand new chapters on: NR in unlicensed spectrum; NR-U in Rel-16; IAB; V2X and sidelink in Rel-16; industrial IoT; IIoT and referring to the URLLC enhancements for PDCCH; RIM/CL; and positioning. Also included are the key radio-related requirements of NR; design principles; technical features of basic NR transmission structure—showing where it was inherited from LTE, where it deviates from it, and the reasons why— NR multi-antenna transmission functionality; detailed description of the signals and functionality of the initial NR access, including signals for synchronization and system information; random access and paging; LTE/NR co-existence in the same spectrum and the benefits of their interworking as one system; and different aspects of mobility in NR. RF requirements for NR are described for BS and UE, the legacy bands, and for the new mm-wave bands.
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.