Austin, Texas
June 14, 2009
June 14, 2009
June 17, 2009
2153-5965
Electrical and Computer
19
14.1332.1 - 14.1332.19
10.18260/1-2--4704
https://peer.asee.org/4704
3104
Sharlene Katz is a Professor in the Department of Electrical and Computer Engineering at California State University, Northridge (CSUN) where she has been for over 25 years. She graduated from the University of California, Los Angeles with B.S. (1975), M.S. (1976), and Ph.D. (1986) degrees in Electrical Engineering. Recently, her areas of research interest have been in engineering education techniques, software defined radio, and neural networks. Dr. Katz is a licensed professional engineer in the state of California.
James Flynn is a part time faculty member in the Department of Electrical and Computer Engineering at California State University, Northridge (CSUN). He holds a B.S. (1977) degree in Electrical Engineering from the Illinois Institute of Technology and a Master of Fine Arts (1981) degree from Northwestern University. He is a partner in a consulting firm specializing in electronics for television and film production. Currently he is developing education tools involving software defined radio (SDR).
Using Software Defined Radio (SDR) To Demonstrate Concepts In Communications and Signal Processing Courses
Abstract
The fundamental course in communications systems included in most electrical engineering programs introduces the concepts of basic analog and/or digital modulation techniques. Teaching modulation theory is mathematical in nature and can be an abstract concept for students. This may often result in low student motivation and comprehension of the subject matter. This paper describes a set of classroom demonstrations developed with software defined radio (SDR) to illustrate the concepts presented in an analog communications course.
Based on feedback from the students in this course, the demonstrations developed increased their understanding and motivation. Cost was minimal and could be nearly zero with available free software and downloadable signals.
I. Introduction
This paper presents a set of classroom demonstrations developed for use in the senior level analog communications course that is common to most electrical engineering programs. The demonstrations are intended to provide motivation to students with little or no practical experience with communications systems. By using software defined radio (SDR), communication systems are demonstrated with signals that are familiar to students. The demonstrations can be used in any classroom or laboratory with minimal cost.
Section II of this paper provides background on some of the issues that faculty currently face when teaching analog communications theory and explains the need for demonstrations in the course. Section III gives an overview of SDR and the features that make it an ideal platform for classroom demonstrations in communications and signal processing. Section IV describes the particular SDR platform (hardware and software) that was used by the authors. Section V presents the demonstrations created. Section VI describes the results of using these demonstrations in a classroom and section VII presents conclusions and plans for future work in this area.
II. Background
Courses on communications theory rely heavily on mathematical models. The abstract nature of the mathematical treatment of modulation/demodulation can be difficult for students to understand. This is particularly true now since most of our students do not have prior hobby and/or work experience with electronics as students in the past have had.
Lacking practical experience, our typical students have more of a need to see that the material they are learning in class is useful in the “real world”. In addition, practical applications of communications theory provide an overall structure in which to place what could be seen as unconnected equations and concepts. Unfortunately, classroom access to commercial
Katz, S., & Flynn, J. (2009, June), Using Software Defined Radio (Sdr) To Demonstrate Concepts In Communications And Signal Processing Courses Paper presented at 2009 Annual Conference & Exposition, Austin, Texas. 10.18260/1-2--4704
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