Behavioral Modeling and Predistortion of Wideband Wireless Transmitters

This book is a must-read for all network planners and other professionals wishing to improve the quality and cost efficiency of 3G and LTE networks In this book, the authors address the architecture of the 2/3G network and the Long Term Evolution (LTE) network. The book proposes analytical models that make the analysis and dimensioning of the most important interfaces, i.e. WCDMA or Iub, possible. Furthermore, the authors include descriptions of fundamental technological issues in 2/3 G networks, basic traffic engineering models and frequent examples of the application of analytical models in the analysis and dimensioning of the interface of cellular networks. The specific knowledge included in the content will enable the reader to understand and then to prepare appropriate programming softwares that will allow them to evaluate quality parameters of cellular networks, i.e. blocking probabilities or call losses. Additionally, the book presents models for the analysis and dimensioning of the Wideband Code Division Multiple Access (WCDMA) radio interface and the Iub interface, both carrying a mixture of Release 99 traffic (R99) and High-Speed Packet Access (HSPA) traffic streams. Finally, the analytical models presented in the book can be also used in the process of modeling and optimization of LTE networks. Key Features: Describes the architecture and the modes of operation of the cellular 2/3/4G systems and the LTE network Covers the traffic theory and engineering within the context of mobile networks Presents original analytical methods that enable their users to dimension selected interfaces of cellular networks Discusses models for the analysis and dimensioning of the Wideband Code Division Multiple Access (WCDMA) radio interface and the Iub interface, both carrying a mixture of Release 99 traffic (R99) and High-Speed Packet Access (HSPA) traffic streams Includes problems as well as an accompanying website containing solutions, software tools and interactive flash animations (http://wiley.teletraffic.pl) This book will be an invaluable guide for professional engineers (radio planning engineers, optimization engineers, transmission engineers, core network engineers, Service Management engineers) working in the areas of mobile wireless networks technology, not only in optimization process, but also in profitability assessment of newly implemented services (i.e. in NPV – Net Present Value analysis), and researchers and scientists. Advanced students in the fields of mobile communications networks and systems will also find this book insightful.

An international panel of experts provide major research issues and a self-contained, rapid introduction to the theory and application of UWB This book delivers end-to-end coverage of recent advances in both the theory and practical design of ultra wideband (UWB) communication networks. Contributions offer a worldwide perspective on new and emerging applications, including WPAN, sensor and ad hoc networks, wireless telemetry, and telemedicine. The book explores issues related to the physical layer, medium access layer, and networking layer. Following an introductory chapter, the book explores three core areas: * Analysis of physical layer and technology issues * System design elements, including channel modeling, coexistence, and interference mitigation and control * Review of MAC and network layer issues, up to the application Case studies present examples such as network and transceiver design, assisting the reader in understanding the application of theory to real-world tasks. Ultra Wideband Wireless Communication enables technical professionals, graduate students, engineers, scientists, and academic and professional researchers in mobile and wireless communications to become conversant with the latest theory and applications by offering a survey of all important topics in the field. It also serves as an advanced mathematical treatise; however, the book is organized to allow non-technical readers to bypass the mathematical treatments and still gain an excellent understanding of both theory and practice.

This book offers a practical guide on how to use and apply channel models for system evaluation In this book, the authors focus on modeling and simulation of multiple antennas channels, including multiple input multiple output (MIMO) communication channels, and the impact of such models on channel estimation and system performance. Both narrowband and wideband models are addressed. Furthermore, the book covers topics related to modeling of MIMO channel, their numerical simulation, estimation and prediction, as well as applications to receive diversity, capacity and space-time coding techniques. Key Features: Contains significant background material, as well as novel research coverage, which make the book suitable for both graduate students and researchers Addresses issues such as key-hole, correlated and non i.i.d. channels in the frame of the Generalized Gaussian approach Provides a unique treatment of generalized Gaussian channels and orthogonal channel representation Reviews different interpretations of scattering environment, including geometrical models Focuses on the analytical techniques which give a good insight into the design of systems on higher levels Describes a number of numerical simulators demonstrating the practical use of this material. Includes an accompanying website containing additional materials and practical examples for self-study This book will be of interest to researchers, engineers, lecturers, and graduate students.

Explores wide-ranging applications of modeling and simulation techniques that allow readers to conduct research and ask «What if??» Principles of Modeling and Simulation: A Multidisciplinary Approach is the first book to provide an introduction to modeling and simulation techniques across diverse areas of study. Numerous researchers from the fields of social science, engineering, computer science, and business have collaborated on this work to explore the multifaceted uses of computational modeling while illustrating their applications in common spreadsheets. The book is organized into three succinct parts: Principles of Modeling and Simulation provides a brief history of modeling and simulation, outlines its many functions, and explores the advantages and disadvantages of using models in problem solving. Two major reasons to employ modeling and simulation are illustrated through the study of a specific problem in conjunction with the use of related applications, thus gaining insight into complex concepts. Theoretical Underpinnings examines various modeling techniques and introduces readers to two significant simulation concepts: discrete event simulation and simulation of continuous systems. This section details the two primary methods in which humans interface with simulations, and it also distinguishes the meaning, importance, and significance of verification and validation. Practical Domains delves into specific topics related to transportation, business, medicine, social science, and enterprise decision support. The challenges of modeling and simulation are discussed, along with advanced applied principles of modeling and simulation such as representation techniques, integration into the application infrastructure, and emerging technologies. With its accessible style and wealth of real-world examples, Principles of Modeling and Simulation: A Multidisciplinary Approach is a valuable book for modeling and simulation courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for researchers and practitioners working in statistics, mathematics, engineering, computer science, economics, and the social sciences who would like to further develop their understanding and knowledge of the field.

Control systems have come to play an important role in the performance of modern vehicles with regards to meeting goals on low emissions and low fuel consumption. To achieve these goals, modeling, simulation, and analysis have become standard tools for the development of control systems in the automotive industry. Modeling and Control of Engines and Drivelines provides an up-to-date treatment of the topic from a clear perspective of systems engineering and control systems, which are at the core of vehicle design. This book has three main goals. The first is to provide a thorough understanding of component models as building blocks. It has therefore been important to provide measurements from real processes, to explain the underlying physics, to describe the modeling considerations, and to validate the resulting models experimentally. Second, the authors show how the models are used in the current design of control and diagnosis systems. These system designs are never used in isolation, so the third goal is to provide a complete setting for system integration and evaluation, including complete vehicle models together with actual requirements and driving cycle analysis. Key features: Covers signals, systems, and control in modern vehicles Covers the basic dynamics of internal combustion engines and drivelines Provides a set of standard models and includes examples and case studies Covers turbo- and super-charging, and automotive dependability and diagnosis Accompanied by a web site hosting example models and problems and solutions Modeling and Control of Engines and Drivelines is a comprehensive reference for graduate students and the authors’ close collaboration with the automotive industry ensures that the knowledge and skills that practicing engineers need when analysing and developing new powertrain systems are also covered.

Explains multi-level models of enterprise systems and covers modeling methodology This book addresses the essential phenomena underlying the overall behaviors of complex systems and enterprises. Understanding these phenomena can enable improving these systems. These phenomena range from physical, behavioral, and organizational, to economic and social, all of which involve significant human components. Specific phenomena of interest and how they are represented depend on the questions of interest and the relevant domains or contexts. Modeling and Visualization of Complex Systems and Enterprises examines visualization of phenomena and how understanding the relationships among phenomena can provide the basis for understanding where deeper exploration is warranted. The author also reviews mathematical and computational models, defined very broadly across disciplines, which can enable deeper understanding. Presents a 10 step methodology for addressing questions associated with the design or operation of complex systems and enterprises Examines six archetypal enterprise problems including two from healthcare, two from urban systems, and one each from financial systems and defense systems Provides an introduction to the nature of complex systems, historical perspectives on complexity and complex adaptive systems, and the evolution of systems practice Modeling and Visualization of Complex Systems and Enterprises is written for graduate students studying systems science and engineering and professionals involved in systems science and engineering, those involved in complex systems such as healthcare delivery, urban systems, sustainable energy, financial systems, and national security.

This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed and latent variables. Basic and Advanced Bayesian Structural Equation Modeling introduces basic and advanced SEMs for analyzing various kinds of complex data, such as ordered and unordered categorical data, multilevel data, mixture data, longitudinal data, highly non-normal data, as well as some of their combinations. In addition, Bayesian semiparametric SEMs to capture the true distribution of explanatory latent variables are introduced, whilst SEM with a nonparametric structural equation to assess unspecified functional relationships among latent variables are also explored. Statistical methodologies are developed using the Bayesian approach giving reliable results for small samples and allowing the use of prior information leading to better statistical results. Estimates of the parameters and model comparison statistics are obtained via powerful Markov Chain Monte Carlo methods in statistical computing. Introduces the Bayesian approach to SEMs, including discussion on the selection of prior distributions, and data augmentation. Demonstrates how to utilize the recent powerful tools in statistical computing including, but not limited to, the Gibbs sampler, the Metropolis-Hasting algorithm, and path sampling for producing various statistical results such as Bayesian estimates and Bayesian model comparison statistics in the analysis of basic and advanced SEMs. Discusses the Bayes factor, Deviance Information Criterion (DIC), and $L_\nu$-measure for Bayesian model comparison. Introduces a number of important generalizations of SEMs, including multilevel and mixture SEMs, latent curve models and longitudinal SEMs, semiparametric SEMs and those with various types of discrete data, and nonparametric structural equations. Illustrates how to use the freely available software WinBUGS to produce the results. Provides numerous real examples for illustrating the theoretical concepts and computational procedures that are presented throughout the book. Researchers and advanced level students in statistics, biostatistics, public health, business, education, psychology and social science will benefit from this book.

The definite guide to the theory, knowledge, technical expertise, and ethical considerations that define the M&S profession From traffic control to disaster management, supply chain analysis to military logistics, healthcare management to new drug discovery, modeling and simulation (M&S) has become an essential tool for solving countless real-world problems. M&S professionals are now indispensable to how things get done across virtually every aspect of modern life. This makes it all the more surprising that, until now, no effort has been made to systematically codify the core theory, knowledge, and technical expertise needed to succeed as an M&S professional. This book brings together contributions from experts at the leading edge of the modeling and simulation profession, worldwide, who share their priceless insights into issues which are fundamental to professional success and career development in this critically important field. Running as a common thread throughout the book is an emphasis on several key aspects of the profession, including the essential body of knowledge underlying the M&S profession; the technical discipline of M&S; the ethical standards that should guide professional conduct; and the economic and commercial challenges today’s M&S professionals face. • Demonstrates applications of M&S tools and techniques in a variety of fields—such as engineering, operations research, and cyber environments—with over 500 types of simulations • Highlights professional and academic aspects of the field, including preferred programming languages, professional academic and certification programs, and key international societies • Shows why M&S professionals must be fully versed in the theory, concepts, and tools needed to address the challenges of cyber environments The Profession of Modeling and Simulation is a valuable resource for M&S practitioners, developers, and researchers working in industry and government. Simulation professionals, including administrators, managers, technologists, faculty members, and scholars within the physical sciences, life sciences, and engineering fields will find it highly useful, as will students planning to pursue a career in the M&S profession. “ …nearly three dozen experts in Modeling and Simulation (M&S) come together to make a compelling case for the recognition of M&S as a profession… Important reading for anyone seeking to elevate the standing of this vital field.” Alfred (Al) Grasso, President & CEO, The MITRE Corporation Andreas Tolk, PhD, is Technology Integrator for the Modeling, Simulation, Experimentation, and Analytics Division of The MITRE Corporation, an adjunct professor in the Department of Engineering Management and Systems Engineering and the Department for Modeling, Simulation, and Visualization Engineering at Old Dominion University, and an SCS fellow. Tuncer ?ren, PhD, is Professor Emeritus of Computer Science at the University of Ottawa. He is an SCS fellow and an inductee to SCS Modeling and Simulation Hall of Fame. His research interests include advancing methodologies, ethics, body of knowledge, and terminology of modeling and simulation.

Modeling and Analysis of Compositional Data presents a practical and comprehensive introduction to the analysis of compositional data along with numerous examples to illustrate both theory and application of each method. Based upon short courses delivered by the authors, it provides a complete and current compendium of fundamental to advanced methodologies along with exercises at the end of each chapter to improve understanding, as well as data and a solutions manual which is available on an accompanying website. Complementing Pawlowsky-Glahn’s earlier collective text that provides an overview of the state-of-the-art in this field, Modeling and Analysis of Compositional Data fills a gap in the literature for a much-needed manual for teaching, self learning or consulting.

This book introduces the state-of-the-art in research in parallel and distributed embedded systems, which have been enabled by developments in silicon technology, micro-electro-mechanical systems (MEMS), wireless communications, computer networking, and digital electronics. These systems have diverse applications in domains including military and defense, medical, automotive, and unmanned autonomous vehicles. The emphasis of the book is on the modeling and optimization of emerging parallel and distributed embedded systems in relation to the three key design metrics of performance, power and dependability. Key features: Includes an embedded wireless sensor networks case study to help illustrate the modeling and optimization of distributed embedded systems. Provides an analysis of multi-core/many-core based embedded systems to explain the modeling and optimization of parallel embedded systems. Features an application metrics estimation model; Markov modeling for fault tolerance and analysis; and queueing theoretic modeling for performance evaluation. Discusses optimization approaches for distributed wireless sensor networks; high-performance and energy-efficient techniques at the architecture, middleware and software levels for parallel multicore-based embedded systems; and dynamic optimization methodologies. Highlights research challenges and future research directions. The book is primarily aimed at researchers in embedded systems; however, it will also serve as an invaluable reference to senior undergraduate and graduate students with an interest in embedded systems research.