Decoding Wireless Communications
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Decoding Wireless Communications
Author: Attaphongse Taparugssanagorn
language: en
Publisher: Cambridge Scholars Publishing
Release Date: 2024-06-21
Step into the captivating context of wireless technology with “Decoding Wireless Communications: Bridging Technology and Everyday Life.” Even if you are new to telecommunication engineering, this book makes the journey accessible and engaging. Through relatable analogies and insightful explanations, complex concepts become clear and relatable. Picture wireless networks as bustling cafes, and diversity techniques as the harmonious interplay of musicians in a band. Each chapter unfolds seamlessly, from combating interference with equalizers to navigating the multitasking marvels of Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM). Explore the boundaries of wireless capacity and glimpse the future of 5G, Artificial Intelligence (AI), and the Internet of Things (IoT). Whether you are a curious beginner or a seasoned professional, this book promises an enlightening journey. With its blend of practical insights and thought-provoking reflections, “Decoding Wireless Communications” is your indispensable guide to thriving in our interconnected world. Prepare to be inspired and equipped with the knowledge to decode the intricacies of wireless technology. Grab your copy now and set forth on a journey of discovery that seamlessly intertwines technology with the fabric of everyday life.
Fundamentals of Wireless Communication
Author: David Tse
language: en
Publisher: Cambridge University Press
Release Date: 2005-05-26
This textbook takes a unified view of the fundamentals of wireless communication and explains cutting-edge concepts in a simple and intuitive way. An abundant supply of exercises make it ideal for graduate courses in electrical and computer engineering and it will also be of great interest to practising engineers.
Machine Learning for Future Wireless Communications
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.