报告主题：通信中的稀疏信号处理Sparse Signal Processing for Communications
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 processing 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 applications 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.
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 signal processing, wireless communications, anddecentralized network optimization. She is an IEEE Fellow. She isChair of the IEEE Signal Processing 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, andAssociate Editor for theIEEE Transactions on Wireless CommunicationsandIEEE Transactions on Signal Processing.