Telecommunications: A Beginner's Guide
Telecommunications: A Beginner's Guide

Author: Hill Associates, Inc.

Publisher: McGraw Hill Professional

Published: 2002-01-01

Total Pages: 540

ISBN-13: 9780072225495

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Written by the seasoned telecommunications training experts at Hill Associates, this book provides you with a step-by-step introduction to the industry, and includes practical hands-on tips and techniques on implementing key technologies. Covers emerging topics such as optical networking, wireless communication, and convergence, and contains blueprints that help bring the technology to life.

Telecommunications
Telecommunications

Author: Resa Azarmsa

Publisher: Routledge

Published: 2013-11-26

Total Pages: 328

ISBN-13: 1135520739

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The objective of this book is to provide a comprehensive introduction to telecommunications and their applications in teaching and learning. It contains up-to-date information about telecommunications, including the latest hardware and software. It discusses the most recent developments in computer networking and how to apply them creatively in the classroom and the school. There is an in-depth discussion of teleconferencing as a way to bring cost-effective instructional material to students. The book also explores distance learning and how it can be expanded to include the home and office as well as the school. There is a detailed presentation on how to ensure computer security in schools to protect records, grades, and other sensitive data. Practical applications and examples are given where appropriate. A directory of on-line educational databases, a lengthy glossary, and an index are included.

Machine Learning and Wireless Communications
Machine Learning and Wireless Communications

Author: Yonina C. Eldar

Publisher: Cambridge University Press

Published: 2022-06-30

Total Pages: 560

ISBN-13: 1108967736

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How can machine learning help the design of future communication networks – and how can future networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most transformative and impactful technologies of our age in this comprehensive book. First, learn how modern machine learning techniques, such as deep neural networks, can transform how we design and optimize future communication networks. Accessible introductions to concepts and tools are accompanied by numerous real-world examples, showing you how these techniques can be used to tackle longstanding problems. Next, explore the design of wireless networks as platforms for machine learning applications – an overview of modern machine learning techniques and communication protocols will help you to understand the challenges, while new methods and design approaches will be presented to handle wireless channel impairments such as noise and interference, to meet the demands of emerging machine learning applications at the wireless edge.

Applications of Machine Learning in Wireless Communications
Applications of Machine Learning in Wireless Communications

Author: Ruisi He

Publisher: Telecommunications

Published: 2019-08

Total Pages: 491

ISBN-13: 1785616579

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This detailed and comprehensive reference considers how to combine the disciplines of wireless communications and machine learning. Coverage includes channel modelling, signal estimation and detection, energy efficiency, cognitive radios, wireless sensor networks, vehicular communications and wireless multimedia communications.

Machine Learning for Future Wireless Communications
Machine Learning for Future Wireless Communications

Author: Fa-Long Luo

Publisher: John Wiley & Sons

Published: 2020-02-10

Total Pages: 490

ISBN-13: 1119562252

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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.