Speaker: Dr Jun Tong, University of Wollongong (UOW), Australia

Time and Date: 10:00-11:30 am, December 19, 2018

Place: Room B415 of Computing Center Building, Handan Campus, Fudan University

Abstract:

Regularisation has proven effective for solving ill-posed inverse problems in high-dimensional signal processing by introducing extra penalties to the solution. One particularly relevant application is in large-scale antenna arrays, which have been intensively studied for high-rate wireless communications and high-resolution sensing systems. Key challenges of applying regularised estimators in practice include the derivation of computationally efficient solutions and the automatic tuning of the regularisation parameters. In this talk, we report some progress in these aspects with examples of data-driven approaches for covariance matrix estimation with low-sample support, low-complexity MIMO detection, and robust channel estimation for hybrid millimetre wave systems. We show that regularised estimators can significantly boost the performance and robustness for large-scale antenna arrays at low costs and further research may be carried out to further exploit their potentials. 

Biography:

Jun received the B.E. and M.E. degrees from the University of Electronic Science and Technology of China (UESTC), and the Ph.D. degree in electronic engineering from City University of Hong Kong. He was a Research Academic at The University of Newcastle, Australia from 2009 to 2011, and an Akademischer Rat with Universitaet Paderborn, Germany, from 2011 to 2013. Jun is currently a Senior Lecturer with the School of Electrical, Computer and Telecommunications Engineering, University of Wollongong (UOW), Australia. His research interests include statistical signal processing and its applications to wireless communication systems.