Bücher der Reihe Signals and Communication Technology

This book investigates the physical layer aspects of high-speed transmission on twisted-pair copper wires, where the most performance-critical components are multi-input multi-output (MIMO) precoding and multi-line spectrum optimization as well as optimized scheduling of the transmission time slots on the fiber to the distribution point (FTTdp) copper link. The book brings theoretical results into the implementation, which requires the introduction of realistic channel models and more practical implementation constraints as found in the copper access network.A good understanding of the transmission medium, twisted-pair telephone cable bundles is the basis for this work. Starting from the analysis of measurement data from twisted-pair cable bundles at high frequencies, it presents a MIMO channel model for the FTTdp network, which allows the characteristic effects of high-frequency transmission on copper cable bundles in simulation to be reproduced and the physical layer transmission methods on the copper channels to be analyzed and optimize.The book also presents precoding optimization for more general power constraints and implementation constraints. The maximization of data rate in a transmission system such as G.fast or VDSL is a combinatorial problem, as the rate is a discrete function of the number of modulated bits. Applying convex optimization methods to the problem offers an efficient and effective solution approach that is proven to operate close to the capacity of the FTTdp channel.In addition to higher data rates, low power consumption is another important aspect of the FTTdp network, as it requires many access nodes that are supplied with power from the subscriber side over the twisted- pair copper wires. Discontinuous operation is a method of quickly adding and removing lines from the precoding group. To implement this, the system switches between different link configurations over time at a high frequency. The transmission times of all lines are jointly optimized with respect to the current rate requirements. Discontinuous operation is used to save power, but also makes it possible to further increase the data rates, taking the current subscriber traffic requirements into account. These methods are compared with theoretical upper bounds, using realistic channel models and conditions of a system implementation. The performance analysis provides deeper insights into implementation complexity trade-offs and the resulting gap to channel capacity.

This book discusses the architecture of modern automated systems for spectrum monitoring including automation components: technical means for spectrum monitoring, special software and engineering infrastructure.

This book provides the first comprehensive overview of the fascinating topic of audio source separation based on non-negative matrix factorization, deep neural networks, and sparse component analysis. The first section of the book covers single channel source separation based on non-negative matrix factorization (NMF). After an introduction to the technique, two further chapters describe separation of known sources using non-negative spectrogram factorization, and temporal NMF models. In section two, NMF methods are extended to multi-channel source separation. Section three introduces deep neural network (DNN) techniques, with chapters on multichannel and single channel separation, and a further chapter on DNN based mask estimation for monaural speech separation. In section four, sparse component analysis (SCA) is discussed, with chapters on source separation using audio directional statistics modelling, multi-microphone MMSE-based techniques and diffusion map methods. The book brings together leading researchers to provide tutorial-like and in-depth treatments on major audio source separation topics, with the objective of becoming the definitive source for a comprehensive, authoritative, and accessible treatment. This book is written for graduate students and researchers who are interested in audio source separation techniques based on NMF, DNN and SCA.

The book systematically introduces the visible light communication (VLC) technology in detail. In addition, a good many experimental results are presented to help readers further understand the VLC technologies. The upper-layer protocols of visible light communication system and the technology trends are also discussed.

This textbook covers the theoretical backgrounds and practical aspects of image, video and audio feature expression, e.g., color, texture, edge, shape, salient point and area, motion, 3D structure, audio/sound in time, frequency and cepstral domains, structure and melody.

This open access book, authored by a world-leading researcher in this field, describes fundamentals of dynamic spectrum management, provides a systematic overview on the enabling technologies covering cognitive radio, blockchain, and artificial intelligence, and offers valuable guidance for designing advanced wireless communications systems.

This book comprehensively covers the important efforts in improving the quality of images in visual cryptography (VC), with a focus on cases with gray scale images.

The subject of this book is theory, principles and methods used in radar algorithm development with a special focus on automotive radar signal processing.

This book provides insights into how deep learning techniques impact language and speech processing applications. The authors discuss the promise, limits and the new challenges in deep learning. The book covers the major differences between the various applications of deep learning and the classical machine learning techniques. The main objective of the book is to present a comprehensive survey of the major applications and research oriented articles based on deep learning techniques that are focused on natural language and speech signal processing. The book is relevant to academicians, research scholars, industrial experts, scientists and post graduate students working in the field of speech signal and natural language processing and would like to add deep learning to enhance capabilities of their work.Discusses current research challenges and future perspective about how deep learning techniques can be applied to improve NLP and speech processing applications;Presents and escalates the research trends and future direction of language and speech processing;Includes theoretical research, experimental results, and applications of deep learning.

In the second part, several schemes of compensation and/or reduction of imperfections are explored, including linearization of power amplifiers, compensation of the characteristics of analog-to- digital converters and CFO compensation for OFDM modulation.

The updated book presents Matlab illustrations on various digital signal processing (DSP) techniques such as random process, time varying wireless system model, and detection and estimation theory used in wireless communication.

This book provides an analysis of the role of fog computing, cloud computing, and Internet of Things in providing uninterrupted context-aware services as they relate to Healthcare 4.0. It also considers aspects required to manage the complexity of fog computing for Healthcare 4.0 and also develops a comprehensive taxonomy.

This book provides current R&D trends and novel approaches in design and analysis of broadband, multiband, and smart antennas for 5G and B5G mobile and wireless applications, as well as the identification of integration techniques of these antennas in a diverse range of devices.

This book presents the design requirements of antenna integration for modern commercial devices such as smartphones, dongles, and access points. High efficiency antennas for 5G base stations is introduced along with a design example on planar all-metallic antenna.

The new edition of this popular book has been transformed into a hands-on textbook, focusing on the principles of wireless sensor networks (WSNs), their applications, their protocols and standards, and their analysis and test tools;