Overview
Authoritative resource systematically introducing JCAS technologies and providing valuable information and knowledge to researchers and engineers Based on over six years of dedicated research to joint communications and sensing (JCAS) by the authors and their collaborators and students, Joint Communications and Sensing is the first book to comprehensively cover the subject of JCAS, which is expected to deliver huge cost and energy savings, and therefore has become a hallmark of future 6G and next generation radar technologies. The book has three parts. Part I presents the basic JCAS concepts and applications and the basic signal processing algorithms to support JCAS. Part II covers communications-centric JCAS designs that describe how sensing can be integrated into communications networks such as 5G and 6G. Part III presents ways to integrate communications in various radar sensing technologies and platforms. Specific sample topics covered in Joint Communications and Sensing include: Three categories of JCAS systems, potential sensing applications of JCAS, signal processing fundamentals, and channel models for communications and radar Frameworks for perceptive mobile networks (PMNs), system modifications to enable PMN sensing, and PMN system issues Orthogonal time-frequency space waveform-based JCAS for IoT, including signal models, echo pre-processing, and target parameter estimation Joint Communications and Sensing provides valuable information and knowledge to researchers and engineers in the communications and radar sensing communities and industries, enabling them to upskill and prepare for JCAS technology research and development. The text is of particular interest to engineers in the wireless communications industry who are pursuing new capabilities in 6G.
- | Author: Kai Wu, J. Andrew Zhang, Yingjie Jay Guo
- | Publisher: Wiley-Ieee Press
- | Publication Date: Dec 08, 2022
- | Number of Pages: 320 pages
- | Language: English
- | Binding: Hardcover
- | ISBN-10: 111998291X
- | ISBN-13: 9781119982913
