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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.
Space-time coding techniques play a major role in modern wireless communication systems since they can achieve very high data transmission rates. Designing efficient algorithms to implement these techniques is a significant challenge, and there is currently a great amount of interest in sphere decoding algorithms in this context. This book will describe efficient algorithms for detection and decoding, focussing on receivers in wireless communication systems. The complexity and design of sphere decoding algorithms will be discussed in detail, and their performance analyzed. The book is aimed at researchers and graduate students of electrical engineering and computer science. It will also appeal to practitioners in the wireless industry.
The high level of technical detail included in standards specifications can make it difficult to find the correlation between the standard specifications and the theoretical results. This book aims to cover both of these elements to give accessible information and support to readers. It explains the current and future trends on communication theory and shows how these developments are implemented in contemporary wireless communication standards. Examining modulation, coding and multiple access techniques, the book is divided into two major sections to cover these functions. The two-stage approach first treats the basics of modulation and coding theory before highlighting how these concepts are defined and implemented in modern wireless communication systems. Part 1 is devoted to the presentation of main L1 procedures and methods including modulation, coding, channel equalization and multiple access techniques. In Part 2, the uses of these procedures and methods in the wide range of wireless communication standards including WLAN, WiMax, WCDMA, HSPA, LTE and cdma2000 are considered. An essential study of the implementation of modulation and coding techniques in modern standards of wireless communication Bridges the gap between the modulation coding theory and the wireless communications standards material Divided into two parts to systematically tackle the topic - the first part develops techniques which are then applied and tailored to real world systems in the second part Covers special aspects of coding theory and how these can be effectively applied to improve the performance of wireless communications systems
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.
Preface. Abbreviations. 1. Introduction to modulation and coding. 2. Principles of linear modulation. 3. Modulation for non-linear systems. 4. Modem design. 5. Principles of FEC Coding. 6. Cyclic block codes. 7. Convolutionals codes. 8. Coded modulation. 9. Modulation and coding on multipath channels. 10. OFDM. 11. Turbo-codes. Appendix 1. Finite field theory. Appendix 2. The MAP algorithm.
Eine vielversprechende Technologie zur Maximierung der Bandbreiteneffizienz in der breitbandigen drahtlosen Kommunikation ist die Raum-Zeit-Kodierung. Theorie und Praxis verbindend, ist dieses Buch die erste umfassende Diskussion von Grundlagen und designorientierten Aspekten von Raum-Zeit-Codes. Single-Carrier und Multi-Carrier-Übertragungen für Einzel- und Mehrnutzerkommunikation werden behandelt.
This book introduces the theoretical elements at the basis of various classes of algorithms commonly employed in the physical layer (and, in part, in MAC layer) of wireless communications systems. It focuses on single user systems, so ignoring multiple access techniques. Moreover, emphasis is put on single-input single-output (SISO) systems, although some relevant topics about multiple-input multiple-output (MIMO) systems are also illustrated. Comprehensive wireless specific guide to algorithmic techniques Provides a detailed analysis of channel equalization and channel coding for wireless applications Unique conceptual approach focusing in single user systems Covers algebraic decoding, modulation techniques, channel coding and channel equalisation
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.
Wireless channels are becoming more and more important, with the future development of wireless ad-hoc networks and the integration of mobile and satellite communications. To this end, algorithmic detection aspects (involved in the physical layer) will become fundamental in the design of a communication system. This book proposes a unified approach to detection for stochastic channels, with particular attention to wireless channels. The core idea is to show that the three main criteria of sequence detection, symbol detection and graph-based detection, can all be described within a general framework. This implies that a detection algorithm based on one criterion can be extended to the other criteria in a systematic manner. Presents a detailed analysis of statistical signal detection for digital signals transmitted over wireless communications Provides a unifying framework for different signal detection algorithms, such as sequence detection, symbol detection and graph-based detection, important for the design of modern digital receivers operating over mobile channels Features the hot topic of graph-based detection Detection Algorithms for Wireless Communications represents a novel contribution with respect to the current literature, with a unique focus on detection algorithms, as such it will prove invaluable to researchers working in academia and industry and in the field of wireless communications, as well as postgraduate students attending advanced courses on mobile communications.