2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). PDF Download

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Publisher:
ISBN: 9781538635124
Category :
Languages : en
Pages :

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Author: IEEE Staff
Publisher:
ISBN: 9781538635131
Category :
Languages : en
Pages :

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The workshop is devoted to advances in signal processing for wireless communications, networking, and information theory

Author: Kumar Vijay Mishra
Publisher: John Wiley & Sons
ISBN: 1119795532
Category : Technology & Engineering
Languages : en
Pages : 453

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Book Description
Signal Processing for Joint Radar Communications A one-stop, comprehensive source for the latest research in joint radar communications In Signal Processing for Joint Radar Communications, four eminent electrical engineers deliver a practical and informative contribution to the diffusion of newly developed joint radar communications (JRC) tools into the sensing and communications communities. This book illustrates recent successes in applying modern signal processing theories to core problems in JRC. The book offers new results on algorithms and applications of JRC from diverse perspectives, including waveform design, physical layer processing, privacy, security, hardware prototyping, resource allocation, and sampling theory. The distinguished editors bring together contributions from more than 40 leading JRC researchers working on remote sensing, electromagnetics, optimization, signal processing, and beyond 5G wireless networks. The included resources provide an in-depth mathematical treatment of relevant signal processing tools and computational methods allowing readers to take full advantage of JRC systems. Readers will also find: Thorough introductions to fundamental limits and background on JRC theory and applications, including dual-function radar communications, cooperative JRC, distributed JRC, and passive JRC Comprehensive explorations of JRC processing via waveform analyses, interference mitigation, and modeling with jamming and clutter Practical discussions of information-theoretic, optimization, and networking aspects of JRC In-depth examinations of JRC applications in cutting-edge scenarios including automotive systems, intelligent reflecting surfaces, and secure parameter estimation Perfect for researchers and professionals in the fields of radar, signal processing, communications, information theory, networking, and electronic warfare, Signal Processing for Joint Radar Communications will also earn a place in the libraries of engineers working in the defense, aerospace, wireless communications, and automotive industries.

Author: Xiaofeng Meng
Publisher: Springer Nature
ISBN: 9811975329
Category : Computers
Languages : en
Pages : 398

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Book Description
This book constitutes refereed proceedings of the 7th China National Conference on Big Data and Social Computing, BDSC 2022, held in Hangzhou, China, from August 11-13, 2022 The 24 full papers and 2 short papers presented in this volume were carefully reviewed and selected from a total of 99 submissions. The papers in the volume are organised according to the following topical headings: urban computing and social governance; artificial intelligence and cognitive science; social network and group behavior; digital society and public security; digital government and public big data

Author: Reginald A. Banez
Publisher: Springer Nature
ISBN: 3030869059
Category : Computers
Languages : en
Pages : 184

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This book covers the basic theory of mean field game (MFG) and its applications in wireless networks. It starts with an overview of the current and future state-of-the-art in 5G and 6G wireless networks. Then, a tutorial is presented for MFG, mean-field-type game (MFTG), and prerequisite fields of study such as optimal control theory and differential games. This book also includes a literature survey of MFG-based research in wireless network technologies such as ultra-dense networks (UDNs), device-to-device (D2D) communications, internet-of-things (IoT), unmanned aerial vehicles (UAVs), and mobile edge networks (MENs). Several applications of MFG and MFTG in UDNs, social networks, and multi-access edge computing networks (MECNs) are introduced as well. Applications of MFG covered in this book are divided in three parts. The first part covers three single-population MFG research works or case studies in UDNs including ultra-dense D2D networks, ultra-dense UAV networks, and dense-user MECNs. The second part centers on a multiple-population MFG (MPMFG) modeling of belief and opinion evolution in social networks. It focuses on a recently developed MPMFG framework and its application in analyzing the behavior of users in a multiple-population social network. Finally, the last part concentrates on an MFTG approach to computation offloading in MECN. The computation offloading algorithms are designed for energy- and time-efficient offloading of computation-intensive tasks in an MECN. This book targets advanced-level students, professors, researchers, scientists, and engineers in the fields of communications and networks. Industry managers and government employees working in these same fields will also find this book useful.

Author: Muhammad Mahtab Alam
Publisher: Springer Nature
ISBN: 3030649911
Category : Medical
Languages : en
Pages : 228

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Book Description
This book constitutes the refereed post-conference proceedings of the 15th International Conference on Body Area Networks, BodyNets 2020, held in Tallinn, Estonia, in October 2020. The conference was held virtually due to the COVID-19 pandemic.The 15 papers presented were selected from 30 submissions and issue new technologies to provide trustable measuring and communications mechanisms from the data source to medical health databases. Wireless body area networks (WBAN) are one major element in this process. Not only on-body devices but also technologies providing information from inside a body are in the focus of this conference. Dependable communications combined with accurate localization and behavior analysis will benefit WBAN technology and make the healthcare processes more effective.

Author: Saim Ghafoor
Publisher: CRC Press
ISBN: 1000416348
Category : Technology & Engineering
Languages : en
Pages : 531

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Book Description
The rapid growth of the data traffic demands new ways to achieve high-speed wireless links. The backbone networks, data centers, mission-critical applications, as well as end-users sitting in office or home, all require ultra-high throughput and ultra-low latency wireless links. Sophisticated technological advancement and huge bandwidth are required to reduce the latency. Terahertz band, in this regard, has a huge potential to provide these high-capacity links where a user can download the file in a few seconds. To realize the high-capacity wireless links for future applications, in this book, different aspects of the Terahertz band wireless communication network are presented. This book highlights the Terahertz channel characteristics and modeling, antenna design and beamforming, device characterization, applications, and protocols. It also provides state-of-the-art knowledge on different communication aspects of Terahertz communication and techniques to realize the true potential of the Terahertz band for wireless communication.

Author: Fa-Long Luo
Publisher: John Wiley & Sons
ISBN: 1119562252
Category : Technology & Engineering
Languages : en
Pages : 490

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Book Description
A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

Author: Antzela Kosta
Publisher: Linköping University Electronic Press
ISBN: 9179298761
Category :
Languages : en
Pages : 69

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Book Description
Advances in wireless communications and networking technology have taken us towards a pervasively connected world in which a vast array of wireless devices, from mobile phones to environmental sensors, seamlessly communicate with each other. In many of these systems the freshness of the transmitted information is of high importance. Characterization of time-critical information can be achieved through the so-called real-time status updates that are messages, encapsulated in packets, carrying the timestamp of their generation. Status updates track time-varying content that needs to be transmitted from the generation point to a remote destination in a network. To quantify the freshness of information in networked systems, a novel metric, different from delay or latency, termed as “age of information” (AoI) has been introduced. In this thesis, we focus on characterizing and controlling age under various communication system setups. The first part of the thesis considers multiple access communication systems and comprises two papers. The first paper, investigates AoI in relation with throughput in a shared access setup with heterogeneous traffic. More specifically, we consider a shared access system consisting of a primary link and a network of secondary nodes, with multipacket reception (MPR) capabilities. To study the joint throughput-timeliness performance, we formulate two optimization problems considering both objectives and provide guidelines for the design of such a multiple access system satisfying both timeliness and throughput requirements. In the second paper, we study the AoI performance in various multiple access schemes, including scheduling and random access. We present an analysis of the AoI with and without packet management at the transmission queue of the source nodes, considering that packet management is the capability to replace unserved packets in the queue whenever newer ones arrive. We incorporate the effect of channel fading and network path diversity in such a system and provide simulation results that illustrate the impact of network operating parameters on the performance of the considered access protocols. The second part of the thesis considers the characterization of AoI and other freshness performance metrics in a point-to-point communication link, again comprising two papers. In the third paper of this thesis, we expand the concept of information ageing by introducing the cost of update delay (CoUD) metric to characterize the cost of having stale information at the destination. Furthermore, we introduce the value of information of update (VoIU) metric that captures the degree of importance of the update received at the destination. We employ queue-theoretic concepts and provide a theoretical analysis and insights into the prospects of cost and value. Finally, in the last paper, we study the properties of a sample path of the AoI process, and we obtain a general formula of its stationary distribution. We relate this result to a discrete time queueing system and provide a general expression of the generating function of AoI in relation with the system time, and the peak age of information (PAoI). To illustrate the applicability of the results, we analyze the AoI in single-server queues with different disciplines and assumptions. We build upon these results to provide a methodology for analyzing general non-linear age functions for this type of systems.

Author: Saideep Tiku
Publisher: Springer Nature
ISBN: 3031267125
Category : Technology & Engineering
Languages : en
Pages : 563

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While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other covered structures, and subterranean facilities such as underground mines, where GPS signals are severely attenuated or totally blocked. As an alternative to GPS for the outdoors, indoor localization using machine learning is an emerging embedded and Internet of Things (IoT) application domain that is poised to reinvent the way we navigate in various indoor environments. This book discusses advances in the applications of machine learning that enable the localization and navigation of humans, robots, and vehicles in GPS-deficient environments. The book explores key challenges in the domain, such as mobile device resource limitations, device heterogeneity, environmental uncertainties, wireless signal variations, and security vulnerabilities. Countering these challenges can improve the accuracy, reliability, predictability, and energy-efficiency of indoor localization and navigation. The book identifies severalnovel energy-efficient, real-time, and robust indoor localization techniques that utilize emerging deep machine learning and statistical techniques to address the challenges for indoor localization and navigation. In particular, the book: Provides comprehensive coverage of the application of machine learning to the domain of indoor localization; Presents techniques to adapt and optimize machine learning models for fast, energy-efficient indoor localization; Covers design and deployment of indoor localization frameworks on mobile, IoT, and embedded devices in real conditions.