Nathan Blaunstein

Christos G. Christodoulou

Antennas and Propogation for Wireless Communication covers the basics of wireless communication system design with emphasis on antennas and propagation. It contains information on antenna fundamentals and the latest developments in smart antennas, as well as the radiation effects of hand-held devices. Antennas and Propogation for Wireless Communication provides a complete discussion of all the topics important to the design of wireless communication systems. Written by acknowledged authorities in their respective fields, the book deals with practical applications and presents real world examples. A solutions manual for college adopters accompanies the text. Ideal for engineers working in communication, antennas, and propagation for telecomm, military, and aerospace applications, as well as students of electrical engineering, this book covers all topics needed for a complete system design.

Terrestrial, Atmospheric and Ionospheric

Radio Propagation and Adaptive Antennas for Wireless Communication Links

Radio Propagation and Adaptive Antennas for Wireless Communication Networks, 2nd Edition, presents a comprehensive overview of wireless communication system design, including the latest updates to considerations of over-the-terrain, atmospheric, and ionospheric communication channels. New features include the latest experimentally-verified stochastic approach, based on several multi-parametric models; all-new chapters on wireless network fundamentals, advanced technologies, and current and modern multiple access networks; and helpful problem sets at the conclusion of each chapter to enhance clarity. The volume’s emphasis remains on a thorough examination of the role of obstructions on the corresponding propagation phenomena that influence the transmission of radio signals through line-of-sight (LOS) and non-line-of-sight (NLOS) propagation conditions along the radio path between the transmitter and the receiver antennas—and how adaptive antennas, used at the link terminals, can be used to minimize the deleterious effects of such obstructions. With its focus on 3G, 4G, MIMO, and the latest wireless technologies, Radio Propagation and Adaptive Antennas for Wireless Communication Networks represents an invaluable resource to topics critical to the design of contemporary wireless communication systems. Explores novel wireless networks beyond 3G, and advanced 4G technologies, such as MIMO, via propagation phenomena and the fundamentals of adapted antenna usage. Explains how adaptive antennas can improve GoS and QoS for any wireless channel, with specific examples and applications in land, aircraft and satellite communications. Introduces new stochastic approach based on several multi-parametric models describing various terrestrial scenarios, which have been experimentally verified in different environmental conditions New chapters on fundamentals of wireless networks, cellular and non-cellular, multiple access networks, new applications of adaptive antennas for positioning, and localization of subscribers Includes the addition of problem sets at the end of chapters describing fundamental aspects of wireless communication and antennas.

Terrestrial, Atmospheric, and Ionospheric

Radio Propagation and Adaptive Antennas for Wireless Communication Networks

Arjun Gupta

Manel Martínez-Ramón

José Luis Rojo-Álvarez

This practical resource provides an overview of machine learning (ML) approaches as applied to electromagnetics and antenna array processing. Detailed coverage of the main trends in ML, including uniform and random array processing (beamforming and detection of angle of arrival), antenna optimization, wave propagation, remote sensing, radar, and other aspects of electromagnetic design are explored. An introduction to machine learning principles and the most common machine learning architectures and algorithms used today in electromagnetics and other applications is presented, including basic neural networks, gaussian processes, support vector machines, kernel methods, deep learning, convolutional neural networks, and generative adversarial networks. Applications in electromagnetics and antenna array processing that are solved using machine learning are discussed, including antennas, remote sensing, and target classification.

Christos G. Christodoulou

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