Books in the Wireless Networks series

This book proposes the novel network envisions and framework design principles, in order to systematically expound the next generation vehicular networks, including the modelling, algorithms and practical applications.

It is divided into three main parts: The first part briefly discusses the fundamentals of FL for wireless networks, while the second part comprehensively examines the design and analysis of wireless FL, covering resource optimization, incentive mechanism, security and privacy.

This book provides a timely and comprehensive study of developing efficient network slicing frameworks in both 5G wireless and core networks.

This book covers connectivity and edge computing solutions for representative Internet of Things (IoT) use cases, including industrial IoT, rural IoT, Internet of Vehicles (IoV), and mobile virtual reality (VR).

Therefore, the emergence of edge computing has been recently developed as a new computing paradigm that can collect and process data at the edge of the network, which brings significant convenience to solving problems such as delay, bandwidth, and off-loading in the traditional cloud computing paradigm.

However, the openness and weak communication characteristics of USNs make underwater localization much more challenging in comparison to terrestrial sensor networks. In this book, we focus on the localization problem in USNs, taking into account the unique characteristics of the underwater environment.

This book provides a comprehensive review and in-depth study on efficient beamforming design and rigorous performance analysis in mmWave networks, covering beam alignment, beamforming training and beamforming-aided caching.

This book provides a timely and comprehensive study of dynamic resource management for network slicing in service-oriented fifth-generation (5G) and beyond core networks. This includes the perspective of developing efficient computation resource provisioning and scheduling solutions to guarantee consistent service performance in terms of end-to-end (E2E) data delivery delay. Network slicing is enabled by the software defined networking (SDN) and network function virtualization (NFV) paradigms. For a network slice with a target traffic load, the E2E service delivery is enabled by virtual network function (VNF) placement and traffic routing with static resource allocations. When data traffic enters the network, the traffic load is dynamic and can deviate from the target value, potentially leading to QoS performance degradation and network congestion. Data traffic has dynamics in different time granularities. For example, the traffic statistics (e.g., mean and variance) can be non-stationary and experience significant changes in a coarse time granularity, which are usually predictable. Within a long time duration with stationary traffic statistics, there are traffic dynamics in small timescales, which are usually highly bursty and unpredictable. To provide continuous QoS performance guarantee and ensure efficient and fair operation of the network slices over time, it is essential to develop dynamic resource management schemes for the embedded services in the presence of traffic dynamics during virtual network operation. Queueing theory is used in system modeling, and different techniques including optimization and machine learning are applied to solving the dynamic resource management problems.Based on a simplified M/M/1 queueing model with Poisson traffic arrivals, an optimization model for flow migration is presented to accommodate the large-timescale changes in the average traffic rates with average E2E delay guarantee, while addressing a trade-off between load balancing and flow migration overhead. To overcome the limitations of Poisson traffic model, the authors present a machine learning approach for dynamic VNF resource scaling and migration. The new solution captures the inherent traffic patterns in a real-world traffic trace with non-stationary traffic statistics in large timescale, predicts resource demands for VNF resource scaling, and triggers adaptive VNF migration decision making, to achieve load balancing, migration cost reduction, and resource overloading penalty suppression in the long run. Both supervised and unsupervised machine learning tools are investigated for dynamic resource management. To accommodate the traffic dynamics in small time granularities, the authors present a dynamic VNF scheduling scheme to coordinate the scheduling among VNFs of multiple services, which achieves network utility maximization with delay guarantee for each service. Researchers and graduate students working in the areas of electrical engineering, computing engineering and computer science will find this book useful as a reference or secondary text. Professionals in industry seeking solutions to dynamic resource management for 5G and beyond networks will also want to purchase this book.

This book covers the basic theory of mean field game (MFG) and its applications in wireless networks.

The cellular networks are necessarily committed to support the data transmission for UAVs, which the authors refer to as Cellular assisted UAV Sensing.

This book addresses the fundamental design and technical challenges for fifth generation (5G) wireless channel models, including multi-frequency bands and multi-scenarios. The book presents a strong vision for 5G wireless communication networks based on current market trends, proven technologies, and future directions. The book helps enable researchers and industry professionals to come up with novel ideas in the area of wireless heterogeneity, to minimize traffic accidents, to improve traffic efficiency, and to foster the development of new applications such as mobile infotainment. The book acts as a comprehensive reference for students, instructors, researchers, engineers, and other professionals, building their understanding of 5G and in designing 5G systems.Addresses fundamental design and technical challenges for 5G wireless channel models;Presents how to create reliable statistical channel models to capture the propagation properties between transmitters and receivers;Pertinent to researchers, engineers, and professionals in 5G.

The authors rely on estimation theory and signal processing to develop SI-cancellation algorithms by generating an estimate of the received SI and subtracting it from the received signal.The authors also cover two new SI-cancellation methods using the new concept of active signal injection (ASI) for full-duplex MIMO-OFDM systems.

This book presents the current research on safety message dissemination in vehicular networks, covering medium access control and relay selection for multi-hop safety message broadcast.

The coexistence and cooperation between terrestrial and satellite networks are of great potential in future communication networks, and satellite radio access networks has already been considered in the fifth-generation (5G) networks to be supported for phase 2.

This book provides a comprehensive picture of mobile big data starting from data sources to mobile data driven applications.

This book provides a comprehensive picture of mobile big data starting from data sources to mobile data driven applications.