Statistical Signal Processing of Extreme Attenuation Measurements Taken by Commercial Microwave Links for Rain Monitoring

Date: 2:30pm, October 13, 2017
Location: EE Conference Room (Mudd 1306)
Speaker: Dr. Jonathan Ostrometzky Electrical Engineering, Tel Aviv University 

Abstract: This research deals with the case where parameter estimation is required, but only observations of extreme values (i.e., the minimum observed value and/or the maximum observed value per interval) are available. Such estimation problem characterizes rain estimation from measurements logged by network managements systems, implemented on commercial microwave links in the backhaul of cellular networks.

Based on a novel analytical approach which we developed in order to approximate the cumbersome expressions of the relevant Fisher information matrices and to produce simple, practical, and solvable forms, a fully applicable workflow of rain estimation will be presented. This new rain estimation workflow uses the available quantized version of the minimum and the maximum measured signal levels (reported at 15-minute intervals) which are produced by commercial microwave links of cellular networks. A demonstration of the established workflow using actual cellular data is presented, and is shown to produce accurate rain estimates, potentially in real time, with no need for training, prior, or side information.

Biography: Jonathan Ostrometzky was born in 1982. He received the B.Sc. (magna cum laude) and the M.Sc. degrees in electrical engineering in 2010 and 2012, respectively, from Tel Aviv University, Tel Aviv, Israel, where he continued toward the Ph.D. degree. He submitted his Ph.D. dissertation in June 2017. He is currently a Postdoctoral Fellow with the School of Electrical Engineering, Tel Aviv University. His current research interests include novel approaches in statistical signal processing for environmental monitoring using commercial microwave links.

500 W. 120th St., Mudd 1310, New York, NY 10027    212-854-3105               
©2014 Columbia University