Software defined radio-based signal detection and rf parameter estimation platform for enhancing electrical and computer engineering curricula
Supported by an NSF TUES type II grant, we have developed a software defined radio (SDR) based signal detection and radio frequency (RF) parameter estimation platform for enhancing electrical and computer engineering curricula. Specifically, we have developed an SDR based signal detection and RF parameter estimation platform which can be adopted by many courses of electrical and computer engineering curricula. This SDR based platform is equipped with a user-friendly graphical user interface (GUI). Students can easily adjust the center frequency and bandwidth of the RF spectrum and choose different signal detection/RF parameter estimation algorithms. We have integrated a suite of signal detection and RF parameter estimation algorithms in the platform, including energy based detection, cyclostationary analysis based detection, fourth order cumulants based detection, etc. The platform is capable of detecting unknown RF signals, estimating their RF parameters such as carrier frequency, symbol rate, and modulation type. This platform can be adopted by many undergraduate and graduate level courses of electrical and computer engineering. The userfriendly GUI of this platform makes it a useful tool to attract high school students and freshmen year students into the STEM fields. The light weight and portable nature of the SDRs allow this platform to be easily transferable from one place to another, making it an attractive tool for capstone senior design teams as well. Through collaboration among the three participating institutions (including a Historically Black College), the developed SDR based signal detection and RF parameter estimation platform will be integrated in undergraduate curricula of all three institutions.
& Wang, B.
(2016). Software defined radio-based signal detection and rf parameter estimation platform for enhancing electrical and computer engineering curricula. ASEE Annual Conference and Exposition, Conference Proceedings, 2016-June.