Title: Data-Driven Calibration for Radio Frequency Communication Systems  

Abstract:  The radio frequency (RF) circuits of wireless communication systems assemble many analog devices, whose parameters have large deviation and could drift with temperature and over time. In large-scale manufacturing, it is difficult for the analog devices thus assembled to satisfy the performance requirements of wireless communication systems, such as power and frequency. Although it is possible to select high-end analog devices in RF circuit assembling to improve the whole system performance, the cost will increase dramatically. Because RF circuits are complex nonlinear systems, it is extremely difficult to model & control the RF circuitry. In this talk, we introduce data-driven methods to calibrate the RF communication systems precisely without modeling. We show that the RF communication system thus calibrated can reduce its transmit power error within 0.25 dB, and reduce its frequency error up to 3 orders. ​ 

Biography: Dr. Quan is a distinguished professor with the College of Electronic and Information Engineering, Shenzhen University, China. He received his Ph.D. in Electrical Engineering from University of California, Los Angeles (UCLA) with highest honors in 2009, and his B.E. in Communications Engineering from Beijing University of Posts and Telecommunications (BUPT), China in 1999. He worked as a Sr. System Engineer in Qualcomm Research Center (QRC) of Qualcomm Inc. (San Diego, CA) during 2008-2012, and as a RF System Architect with Apple Inc. (Cupertino, CA) during 2012-2015. Dr. Quan had contributed to IEEE 802.11ac/ah standards with over 30 U.S. issued patents and published over 60 papers in wireless communications and signal processing. Dr. Quan was the recipient of UCLA Outstanding Ph.D. Award in 2009, IEEE Signal Processing Society Best Paper Award in 2012, China National Excellent Young Scientist Foundation in 2016, and First Prize Technology Innovation Award by China Institute of Communications in 2020. His current research interests include wireless communication systems, RF system calibration and measurement, data-driven signal processing, and machine learning.