Prof. Zhiqiang Wu, Wright State University

 

Prof. Zhiqiang Wu, Wright State University

Speaker's bio:
Dr. Zhiqiang Wu received his B.S. from Beijing University of Posts and Telecommunications in 1993, M.S. from Peking University in 1996, and Ph.D. from Colorado State University in 2002, all in Electrical Engineering. He had worked for Chinese Academy for Telecommunication Technologies from 1996 to 1998. He had taught at West Virginia University Institute of Technology as an assistant professor from 2003 to 2005. He joined Department of Electrical Engineering of Wright State University in 2005 where he currently serves as full professor, director of Broadband, Mobile and Wireless Networking Laboratory, and director of Wright Center for Sensor System Engineering. Dr. Wu co-authored one of the first books on multi-carrier transmission technologies for communications; he is also the major author of CDMA network management standard of China. Dr. Wu has published more than 150 referred papers in journals and conferences.

Speech title:
Cognitive RF - A Universal Framework for Cognitive Communication, Radar, EW and Navigation

Speech abstract:
Cognitive Radio (CR) has been proposed to address the spectrum congestion in communications. The spectrum congestion problem also affects other RF application such as Radar, Navigation and Electronic Warfare (EW). Recently, the concept of cognitive radio has been adopted by different communities dealing with RF signals: CR and DSA in communication, cognitive Radar/DSA Radar for radar application, cognitive GPS in Navigation and cognitive EW, to name a few. However, current research and development in these areas has been done separately, and functions of different RF applications reside on separated devices. To achieve the best spectrum efficiency, these research areas need to be integrated together to create a universal Cognitive RF platform. We will present our recent work and view on such a universal Cognitive RF platform and how to integrate spectrum sensing, RF signal detection/classification, RF signal parameter estimation, RF watermarking, frequency agile waveform generation technologies together to achieve ultimate spectrum efficient cognitive RF system. We will also present software defined radio implementation of some of the proposed technologies. Part of the SDR implementation was demoed at IEEE Globecom and received the Best Demo Award.