Based on the author's extensive research, this book sets forth tested and proven electromagnetic modeling and simulation methods for analyzing signal and power integrity as well as electromagnetic interference in large complex electronic interconnects, multilayered package structures, integrated circuits, and printed circuit boards. Readers will discover the state of the technology in electronic package integration and printed circuit board simulation and modeling. In addition to popular full-wave electromagnetic computational methods, the book presents new, more sophisticated modeling methods, offering readers the most advanced tools for analyzing and designing large complex electronic structures.

Plasmonic nanostructures provide new ways of manipulating the flow of light with nanostructures and nanoparticles exhibiting optical properties never before seen in the macro-world. Covering plasmonic technology from fundamental theory to real world applications, this work provides a comprehensive overview of the field. Discusses the fundamental theory of plasmonics, enabling a deeper understanding of plasmonic technologyDetails numerical methods for modeling, design and optimization of plasmonic nanostructuresIncludes step-by-step design guidelines for active and passive plasmonic devices, demonstrating the implementation of real devices in the standard CMOS nanoscale electronic-photonic integrated circuit to help cut design, fabrication and characterisation time and costIncludes real-world case studies of plasmonic devices and sensors, explaining the benefits and downsides of different nanophotonic integrated circuits and sensing platforms.Ideal for researchers, engineers and graduate students in the fields of nanophotonics and nanoelectronics as well as optical biosensing.

This brief explores the utilization of large antenna arrays in massive multiple-input-multiple-output (MIMO) for both interference suppression, where it can improve cell-edge user rates, and for wireless backhaul in small cell networks, where macro base stations can forward data to small access points in an energy efficient way. Massive MIMO is deemed as a critical technology for next generation wireless technology. By deploying an antenna array that has active elements in excess of the number of users, massive MIMO not only provides tremendous diversity gain but also powers new aspects for network design to improve performance.

Direct communication between user equipment (UE) – termed device-to-device (D2D) communication – is envisioned as an intriguing solution to meet the growing demand for local wireless service in fifth generation (5G) networks. Taking advantage of physical proximity, D2D communication is blazing the trail for a flexible infrastructure and boasts the potential benefits of high spectral efficiency, low power consumption, and reduced end-to-end latency. Meanwhile, the heterogeneous network has been emerging as another promising technology for 5G, where by overlaying macrocells with a large number of small-cell access points (APs), it can provide higher coverage and throughput. The idea of using D2D communication to perform mobile relaying in a heterogeneous network is attractive, since together with the better link quality provided by the heterogeneous network in the first hop, D2D communication is able to provide flexible relay selection and enhanced link quality in the second hop, and an overall throughput improvement is therefore foreseeable. However, a problem of fairness arises as the UE relay (UER) needs to consume power to forward information to other UEs. One way to address this issue is to use energy harvesting (EH) technology, which enables devices to harvest energy from their surrounding environments. By adopting EH techniques at each UE, devices can harvest energy from the surrounding environment and use only the harvested energy for relaying, thus preventing power loss from their own battery. In this chapter, we try to coalesce EH technology, D2D communication, and the heterogeneous network into one called the D2D-communication-provided EH heterogeneous network (D2D-EHHN), and investigate the effect of different network parameters as well as provide design insights.

D2D communication has been proposed as a new way to enhance network performance by allowing UEs to communicate directly with their corresponding destinations instead of using a base station (BS) or AP [1–3]. To realize the potential advantages of D2D communication, efforts also need to be made to address the challenges that abound, including peer discovery, mode selection, and interference management in shared networks. In response, various solutions have been proposed. In particular, for resource management, methods to enhance the network throughput include allocating optimal proportions of time [4, 5] or spectrum [6] to activate D2D communication, and joint spectrum scheduling and power control [7].

Massive multiple-input multiple-output (MIMO) employs hundreds of antenna elements at the base station (BS) to serve tens of users simultaneously at the same time-frequency resource block. This chapter proposes a downlink heterogeneous cellular network (HCN) where the user location as well as the deployment of multi-antenna macro and small BSs are modeled as independent Poisson point processes (PPPs). It introduces the HCN framework, the line-of-sight (LOS)/non-line-of-sight (NLOS) transmission model, and the user association policy. The chapter derives a tight approximation of the average downlink rate accounting for channel estimation with uplink training. It provides the optimal small cell density that maximizes the average downlink rate, which can be used as a guideline for practical small cell deployment. Moreover, the optimal bias factor is also provided for reference of the practical massive MIMO configuration. The chapter provides numerical results to validate the analytical results and further study the performance of the HCN.

This brief explores the utilization of large antenna arrays in massive multiple-input-multiple-output (MIMO) for both interference suppression, where it can improve cell-edge user rates, and for wireless backhaul in small cell networks, where macro base stations can forward data to small access points in an energy efficient way. Massive MIMO is deemed as a critical technology for next generation wireless technology. By deploying an antenna array that has active elements in excess of the number of users, massive MIMO not only provides tremendous diversity gain but also powers new aspects for network design to improve performance.

To take full advantage of the ultra-dense architecture and efficiently serve the traffic with spatiotemporal fluctuation, the transmission mechanisms should be redesigned under the constraints of backhaul and energy consumption. In this chapter, we summarize and classify the spatiotemporal arrival properties of different traffic in ultra-dense networks, and optimize several promising technologies to match the traffic. A new approach based on combining stochastic geometry and queueing theory is proposed to provide a useful guidance for the design of ultra-dense networks.

At the forefront of cutting-edge technologies, this text provides a comprehensive treatment of a crucial network performance metric, ushering in new opportunities for rethinking the whole design of communication systems. Detailed exposition of the communication and network theoretic foundations of Age of Information (AoI) gives the reader a solid background, and discussion of the implications on signal processing and control theory shed light on the important potential of recent research. The text includes extensive real-world applications of this vital metric, including caching, the Internet of Things (IoT), and energy harvesting networks. The far-reaching applications of AoI include networked monitoring systems, cyber-physical systems such as the IoT, and information-oriented systems and data analytics applications ranging from the stock market to social networks. The future of this exciting subject in 5G communication systems and beyond make this a vital resource for graduate students, researchers and professionals.

Small cell networks are deemed one of the key solutions for next-generation (5G) wireless networks. In such networks, along with the spatial densification of access points, temporal traffic can also vary largely from cell to cell. To this end, a complete understanding of the impact from spatial and temporal aspects is thus essential for network operators to adequately advance the deployment of small cell networks. In this article, based on stochastic geometry and queuing theory, we develop a mathematical framework that captures the interplay between the spatial location of small access points (SAPs), which determines the magnitude of mutual interference, and their temporal traffic dynamic. We derive a tractable expression for the signal-to-interference-plus-noise ratio (SINR) distribution, as well as the mean delay distributions under two different scheduling policies, i.e. the random scheduling and round robin. We also verify the accuracy of our mathematical analysis via simulations. Based on our analysis, we find a number of useful guidelines for the deployment of small cell networks.

Concrete is, both practically and metaphorically, one of the major civil-engineering materials supporting modern society. But both concrete technology, and its structures, face daunting challenges arising from environmental erosion and other natural, and man-made, hazards.