Sparse Signal Processing for Communications
Speaker: Prof. Zhi Tian, George Mason University
Time and Date: 15:00-16:00 pm, July 02, 2018
Place: Room B415 of Computing Center Building, Handan Campus, Fudan University
Abstract:
Sparse signal processing has demonstrated its usefulness in wireless communications over recent years. In the emerging era of data deluge, wireless systems such as 5G and Internet of Things (IoT) have to be able to sense and process an unprecedentedly large amount of data in real time, which render traditional communication and signal processing_ techniques inefficient or inapplicable. Meanwhile, there are exciting new developments on the theory and algorithms of sparse signal processmg and compressive sensing, which offer powerful tools to effectively deal with high-dimensional signals, large-size problems, and big-volume data. This talk presents recent development on sparse signal processing principles and techniques as applied to various wireless applcations where signal and information acquisition costs are high, such as wideband spectrum sensing in cognitive radios and sparse channel estimation using large-antenna arrays in both millimeter-wave communication systems and IoT applications.
Biography:
Dr. Zhi Tian has been a Professor in the Electrical and Computer Engineering Department of George Mason University since 2015. Previously she was on the faculty of Michigan Technological University. Her research interests lie in statistical signl processing, wireless communications, and decentralized network optimization. She is an IEEE Fellow. She is Chair of the IEEE Signal Processmg Society Big Data Special Interest Group She was General Co-Chair of the IEEE GlobalSIP Conference in 2016. She served as an IEEE Distinguished Lecturer, and Associate Editor for the IEEE Transactions on Wireless Communications and IEEE Transactions on Signal Processing.