Bøger i Signals and Communication Tech serien

This book presents state-of-the-art trends in reconfigurable active and passive planar antennas and their applications in wireless communication systems operating in the frequency band 5-6 GHz. Due to various key features such as multifunction antenna design, compactness, planar nature, and low cost, these technologies are becoming popular for current and future wireless applications. This book discusses different novel antenna designs and their working principles in detail. The modern and future wireless systems require wideband antennas to accommodate various channels in a single band or in separate bands. The carrier aggregation (CA) has been introduced in the modern wireless systems such as LTE-advanced systems and 5G./6G. In CA, a device can use several channels for transmission and reception. The used channels can exist in the same frequency band (intra-band CA) or in distinct bands (inter-band CA). To accommodate more channels, more bandwidth is required within the operating band. For portable devices, circularly polarized (CP) antennas are more advantageous over linearly polarized antennas since in CP antennas, there is low risk of misalignment and, hence encountering interference. Circularly polarized antenna also provides higher link reliability for the portable devices. To provide high data rates, more bandwidth is needed to accommodate more channels. Various multifunction, compact, and wideband antennas for plethora of applications are addressed in detail in this book. The scope of developing reconfigurable active antennas for application in beam switching, beam steering, wireless charging, security systems, etc., is described. This book concludes by giving glimpses of antenna requirements for future wireless communication systems.

This book covers network analysis and architecture for large-scale computer network planning. Networks and the Internet are essential for modern industries and societies. Building a new network, upgrading an existing network, or planning to use a public network requires integrating various network mechanisms and technologies in a cohesive fashion. This demands a deep understanding of the concepts, principles, processes, approaches, and good practices of advanced network planning. More specifically, emphasizing service-based networking, the book introduces structured processes for network planning, provides systematic approaches for network analysis and architecture, develops network planning specifications, and discusses high-level network architectural models from various perspectives. It also offers detailed discussions on component-based architecture about addressing, routing, performance, management, and security and privacy. Recent developments in data centers, virtualization,and cloud are also embedded into the network architecture. Moreover, the book includes a comprehensive introduction to building practical TCP/IP network communications via sockets with practical examples. The book is suitable for use as a textbook for senior undergraduate and postgraduate students or as a reference book for network practitioners looking to develop or enhance their skills in network planning.

This textbook covers fundamental topics in Telecommunication including Channel Modeling, Modulation/Demodulation, Channel Coding/Decoding, Multicarrier, Capacity, Antenna Arrays, Diversity, and 4G/5G. It will also cover advanced topics such as High-Resolution Spectral Estimation, Reconfigurable Intelligent Surfaces, Index Modulation, Full-Duplex, and Millimeter Wave. This book will mainly target engineering students (both graduate and advanced undergraduate) who are new to the fields of Communication and Signal Processing and are struggling to understand the fundamental concepts. This book will help the students step by step by introducing the concepts first in their most basic form and then providing the code that the students can experiment with. It contains pedagogical elements such as chapter introductions, end-of-chapter questions and numerical problems, MATLAB/Octave/Python code, figures and tables, and a website (raymaps.com) for feedback and interaction. It will not only be helpful for undergraduate and graduate students but also for professional engineers and hobbyists.

This book addresses the issues with privacy and security in Internet of things (IoT) networks which are susceptible to cyber-attacks and proposes deep learning-based approaches using artificial neural networks models to achieve a safer and more secured IoT environment. Due to the inadequacy of existing solutions to cover the entire IoT network security spectrum, the book utilizes artificial neural network models, which are used to classify, recognize, and model complex data including images, voice, and text, to enhance the level of security and privacy of IoT. This is applied to several IoT applications which include wireless sensor networks (WSN), meter reading transmission in smart grid, vehicular ad hoc networks (VANET), industrial IoT and connected networks. The book serves as a reference for researchers, academics, and network engineers who want to develop enhanced security and privacy features in the design of IoT systems.

This book introduces the basic principles underlying the design and analysis of the digital communication systems that have heralded the information revolution. One major goal of the book is to demonstrate the role of the digital communication principles in a wide variety of data science applications, including community detection, computational biology, speech recognition and machine learning. One defining feature of this book is to make an explicit connection between the communication principles and data science problems, as well as to succinctly deliver the ¿story¿ of how the communication principles play a role for trending data science applications. All the key ¿plots¿ involved in the story are coherently developed with the help of tightly coupled exercise problem sets, and the associated fundamentals are explored mostly from first principles. Another key feature is that it includes programming implementation of a variety of algorithms inspired by fundamentals, together with a brief tutorial of the used programming tools. The implementation is based on Python and TensorFlow. This book does not follow a traditional book-style organization, but is streamlined via a series of lecture notes that are intimately related, centered around coherent storylines and themes. It serves as a textbook mainly for a junior- or senior-level undergraduate course, yet is also suitable for a first-year graduate course. Readers benefit from having a good background in probability and random processes, and basic familiarity with Python. But the background can be supplemented by almost self-contained materials, as well as by numerous exercise problems intended for elaborating on non-trivial concepts. In addition, Part III for data science applications should provide motivation and insights to students and even professional scientists who are interested in the field.