Title: Sparse sampling using coprime (quadratic) integers

基于（二次）互素整数的稀疏采样

Abstract:

Over the past few years, there has been increased interests in the study of sparse arrays and their applications in sonar, radar and communications. These sparse arrays have simple implementation structure and the difference (or sum) co-arrays are larger than those of a uniform linear array. Hence, they can identify many more sources than the number of physical sensors used.  This talk will focus on the basic concept and recent developments on sparse sampling using 1D coprime array or 2D lattice. In particular, a novel 1D coprime array will be presented with reduced number of sensors than existing work . Construction of 2D coprime sampling using quadratic integers will be introduced. Discussions on their applications in multiuser detection of Massive MIMO system will also be included. 

Short bio:

Dr. Lu Gan received her B. Eng and M. Eng. degrees from South East University, China and the Ph.D degree from Nanyang Technological University, Singapore in 1998, 2000 and 2004 respectively. She is currently a senior lecturer (equivalent to associate professor) in Brunel University, London. Before she joined Brunel University in 2008, she has been on the faculties with The University of Newcastle (2004-2006), Australia and University of Liverpool, UK (2006-2007). From 2003 to 2004, she was a research associate in Centre for Signal Processing, Nanyang Technological University.

Dr. Gan’s research interests include fundamental signal processing theories and their applications in image/video coding and processing, non-destructive terahertz and ultrasound imaging, machine learning and wireless communications etc.