This one-of-a-kind new resource presents cognitive radio from an antenna design perspective and introduces the concept of cognitive radio as a protocol that benefits from under-utilized regions of the spectrum. This book covers topics that govern the operation of a cognitive radio and discusses the use of reconfigurable antennas, reconfigurable filtennas, and MIMO antennas for cognitive radio. The analysis and design of different antenna systems are presented, compared and evaluated. New approaches to improve spectrum efficiency are explored by demonstrating how to design software controlled cognitive radio antenna systems. This new resource shows how to communicate using either interweave or underlay cognitive radio and demonstrates the benefits of designing appropriate sensing and communicating antennas.
Youssef Tawk is an assistant professor at Notre Dame University Louaize, Lebanon. He received a Ph.D. in electricalengineering and completed a post-doc fellowship from the University of New Mexico.Joseph Costantine is an assistant professor at the American University of Beirut, Lebanon. He received a Ph. D. inelectrical engineering from the University of New Mexico. Christos G. Christodoulou is a Fellow member of IEEE and adistinguished professor of electrical and computer engineering at the University of New Mexico. He is the recipient ofthe 2010 IEEE John Krauss Antenna Award for his work on reconfigurable fractal antennas, the Lawton-Ellis Award andthe Gardner Zemke Professorship at the University of New Mexico. He holds a M.S. and a Ph.D. in Electrical Engineeringfrom North Carolina State University. Christos is the series editor of antennas at Artech House.
Introduction to Cognitive Radio; Software Defined Radio and Cognitive Radio: An Overall Systems Overview; Antenna Design Requirements for Cognitive Radio; Wideband Sensing Antennas for Cognitive Radio; Communicating Reconfigurable Antennas for Cognitive Radio; Reconfigurable Filtenna for Cognitive Radio; Implementation of MIMO Antennas on Cognitive Radio; Machine Learning Implementation in Cognitive Radio; Cognitive Radio for Radar and Space Applications; The Future of Cognitive Radio.