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Board 16: Software Defined Radio-based Mixed Signal Detection Laboratories for Enhancing Undergraduate Communication and Networking Curricula

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Conference

2018 ASEE Annual Conference & Exposition

Location

Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

NSF Grantees Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count

14

Permanent URL

https://peer.asee.org/29963

Download Count

61

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Paper Authors

biography

Zhiqiang Wu Wright State University

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Dr. Zhiqiang Wu received his BS from Beijing University of Posts and Telecommunications in 1993, MS from Peking University in 1996, and PhD from Colorado State University in 2002, all in electrical engineering. He has worked at West Virginia University Institute of Technology as assistant professor from 2003 to 2005. He joined Wright State University in 2005 and currently serves as full professor. Dr. Wu is the author of national CDMA network management standard of China. He also co-authored one of the first books on multi-carrier transmission for wireless communication. He has published more than 100 papers in journals and conferences. He has served as Chair of Acoustic Communication Interest Group of IEEE Technical Committee on Multimedia Communications. His research has been supported by the National Science Foundation, Air Force Office of Scientific Research, Air Force Research Laboratory, Office of Naval Research, and NASA. His work on software defined radio implementation of cognitive radio won the Best Demo Award at IEEE Globecom 2010.

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Bin Wang Wright State University

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Prof. Bin Wang earned his Ph.D. from the Ohio State University in 2000. He joined the Wright State University in September 2000, where he is currently full professor of computer science and engineering. His research interests include optical networks, real-time computing, mobile and wireless networks, cognitive radio networks, trust and information security, and semantic web. He is a recipient of the US Department of Energy Career Award. His research has been supported by US Department of Energy, National Science Foundation, Air Force Office of Scientific Research, Air Force Research Laboratories, Ohio Supercomputer Center, and the State of Ohio.

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Chi-Hao Cheng Miami University

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Dr. Chi-Hao Cheng received the B.S. degree in control engineering from National Chiao Tung University, Taiwan in 1991, and the M.S. and Ph.D. degrees from The University of Texas at Austin in 1996 and 1998 respectively, both in Electrical and Computer Engineering. He is currently a professor in the Department of Electrical and Computer Engineering at Miami University, Ohio. His primary professional interests lie in signal processing algorithm development and its applications in numerous communications system and component development including wireless and optical communications systems. He is co-inventors of three US patents.

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Deng Cao Central State University

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Dr. Deng Cao received his Ph.D in Computer Science from West Virginia University in 2013. He also earned two master degrees in Statistics and Physics from West Virginia University. Dr. Cao joined Central State University in 2013 and currently serves as an assistant professor in the department of Mathematics and Computer Science. His research interests include computer vision, pattern recognition, machine learning, and advanced biometrics.
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Zhiping Zhang Wright State University

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Zhiping Zhang received his B.S. degree in electrical engineering from Nankai University, Tianjin, China, in 2001, M.S. and Ph.D. degrees in intelligence science from Peking University, Beijing, China, in 2004 and 2011 respectively. From 2011 to 2013, he was a Postdoctoral Research Fellow at the Department of Computer Science and Technology, Peking University. Since 2013, he has served as a research faculty member and co-director of Broadband, Mobile and Wireless Networking Laboratory at the Department of Electrical Engineering of Wright State University.

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Abstract

Supported by a NSF TUES type II project, we have developed a series of software defined radio (SDR) based mixed signal detection laboratories for enhancing undergraduate communication and networking curricula. In our previous NSF funded CCLI project “Evolvable wireless laboratory design and implementation for enhancing undergraduate wireless engineering education”, we have developed and demonstrated the first nationwide example of evolvable SDR based laboratories for three existing undergraduate courses. In this project, we are developing new lab components that can be adopted by multiple courses ranging from freshman year introductory course to senior year capstone design projects. Specifically, in this paper, we report the development of a SDR based mixed radio frequency signal detection platform with a graphical user interface (GUI). This user-friendly GUI will allow students to adjust RF parameters such as carrier frequency, symbol rate, pulse shaping filter, etc, and mix multiple RF signals together. Additionally, students are able to observe the transmitted signal in both time and frequency at both transmitter and receiver. At receiver side, the SDR based platform also provides students the functionality of performing RF signal detection via different detection methods including energy based detection, waveform based detection, and cyclostationary analysis based detection. It is shown that by exploiting sophisticated signal processing techniques such as cyclostationary analysis, mixed RF signal components can be detected and identified. Through collaboration among the three participating institutions including an HBCU, the developed SDR based platform will be integrated in undergraduate curricula of all three institutions.

Wu, Z., & Wang, B., & Cheng, C., & Cao, D., & Zhang, Z. (2018, June), Board 16: Software Defined Radio-based Mixed Signal Detection Laboratories for Enhancing Undergraduate Communication and Networking Curricula Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/29963

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