Even as newer cellular technologies and standards emerge, many of the fundamental principles and the components of the cellular network remain the same. Presenting a simple yet comprehensive view of cellular communications technologies, Cellular Communications provides an end-to-end perspective of cellular operations, ranging from physical layer details to call set-up and from the radio network to the core network. This self-contained source for practitioners and students represents a comprehensive survey of the fundamentals of cellular communications and the landscape of commercially deployed 2G and 3G technologies and provides a glimpse of emerging 4G technologies.
Radio Resource Management in Cellular Systems is the first book to address the critical issue of radio resource management in emerging (i.e., third generation and beyond) wireless systems. This book presents novel approaches for the design of high performance handoff algorithms that exploit attractive features of several existing algorithms, provide adaptation to dynamic cellular environment, and allow systematic tradeoffs among different system characteristics. Efficient handoff algorithms cost-effectively enhance the capacity and quality of service (QoS) of cellular systems. A comprehensive foundation of handoff and related issues of cellular communications is given. Tutorial-type material on the general features of 3G and 3.5G wireless systems (including CDMA2000, UMTS, and 1xEV-DO) is provided. Key elements for the development of simulators to study handoff and overall RF performance of the integrated voice and data cellular systems (including those based on CDMA) are also described. Finally, the powerful design tools of neural networks and fuzzy logic are applied to wireless communications, so that the generic algorithm approaches proposed in the book can be applied to many other design and development areas. The simulation models described in the book represent a single source that provides information for the performance evaluation of systems from handoff and resource management perspectives. Radio Resource Management in Cellular Systems will prove a valuable resource for system designers and practicing engineers working on design and development of third generation (and beyond) wireless systems. It may also be used as a text for advanced-level courses in wireless communications and neural networks.
Even as newer cellular technologies and standards emerge, many of the fundamental principles and the components of the cellular network remain the same. Presenting a simple yet comprehensive view of cellular communications technologies, Cellular Communications provides an end-to-end perspective of cellular operations, ranging from physical layer details to call set-up and from the radio network to the core network. This self-contained source for practitioners and students represents a comprehensive survey of the fundamentals of cellular communications and the landscape of commercially deployed 2G and 3G technologies and provides a glimpse of emerging 4G technologies.
Radio Resource Management in Cellular Systems is the first book to address the critical issue of radio resource management in emerging (i.e., third generation and beyond) wireless systems. This book presents novel approaches for the design of high performance handoff algorithms that exploit attractive features of several existing algorithms, provide adaptation to dynamic cellular environment, and allow systematic tradeoffs among different system characteristics. Efficient handoff algorithms cost-effectively enhance the capacity and quality of service (QoS) of cellular systems. A comprehensive foundation of handoff and related issues of cellular communications is given. Tutorial-type material on the general features of 3G and 3.5G wireless systems (including CDMA2000, UMTS, and 1xEV-DO) is provided. Key elements for the development of simulators to study handoff and overall RF performance of the integrated voice and data cellular systems (including those based on CDMA) are also described. Finally, the powerful design tools of neural networks and fuzzy logic are applied to wireless communications, so that the generic algorithm approaches proposed in the book can be applied to many other design and development areas. The simulation models described in the book represent a single source that provides information for the performance evaluation of systems from handoff and resource management perspectives. Radio Resource Management in Cellular Systems will prove a valuable resource for system designers and practicing engineers working on design and development of third generation (and beyond) wireless systems. It may also be used as a text for advanced-level courses in wireless communications and neural networks.
Create applications using Industry 4.0. Discover how artificial intelligence (AI) and machine learning (ML) capabilities can be enhanced using the Internet of things (IoT) and secured using Blockchain, so your latest app can be not just smarter but also more connected and more secure than ever before. This book covers the latest easy-to-use APIs and services from Microsoft, including Azure IoT, Cognitive Services APIs, Blockchain as a Service (BaaS), and Machine Learning Studio. As you work through the book, you’ll get hands-on experience building an example solution that uses all of these technologies—an IoT suite for a smart healthcare facility. Hosted on Azure and networked using Azure IoT, the solution includes centralized patient monitoring, using Cognitive Services APIs for face detection, recognition, and tracking. Blockchain is used to create trust-based security and inventory management. Machine learning is used to create predictive solutions to proactively improve quality of life. By the end of the book, you’ll be confident creating richer and smarter applications using these technologies. What You’ll Learn Know the technologies underpinning Industry 4.0 and AI 2.0 Develop real-time solutions using IoT in Azure Bring the smart capabilities of AI 2.0 into your application using a simple API call Host and manage your solution on Azure Understand Blockchain as a Service Capture and analyze data on the fly Make predictions using existing data Who This Book Is For Novice and intermediate .NET developers and architects who want to learn what it takes to create a modern or next-generation application
Get introduced to the world of artificial intelligence with this accessible and practical guide. Build applications that make intelligent use of language and user interaction to better compete in today’s marketplace. Discover how your application can deeply understand and interpret content on the web or a user’s machine, intelligently react to direct user interaction through speech or text, or make smart recommendations on products or services that are tailored to each individual user. With Microsoft Cognitive Services, you can do all this and more utilizing a set of easy-to-use APIs that can be consumed on the desktop, web, or mobile devices. Developers normally think of AI implementation as a tough task involving writing complex algorithms. This book aims to remove the anxiety by creating a cognitive application with a few lines of code. There is a wide range of Cognitive Services APIs available. This book focuses on some of the most useful and powerful ways that your application can make intelligent use of language. Artificial Intelligence for .NET: Speech, Language, and Search will show you how you can start building amazing capabilities into your applications today. What You'll Learn Understand the underpinnings of artificial intelligence through practical examples and scenarios Get started building an AI-based application in Visual Studio Build a text-based conversational interface for direct user interaction Use the Cognitive Services Speech API to recognize and interpret speech Look at different models of language, including natural language processing, and how to apply them in your Visual Studio application Reuse Bing search capabilities to better understand a user’s intention Work with recommendation engines and integrate them into your apps Who This Book Is For Developers working on a range of platforms, from .NET and Windows to mobile devices. Examples are given in C#. No prior experience with AI techniques or theory is required.
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