This talk describes an optimization framework for a class of constant modulus (CM) problems, which covers binary constraints, discrete phase constraints, semi-orthogonal matrix constraints, non-negative semi-orthogonal matrix constraints, and several types of binary assignment constraints. Capitalizing on the basic principles of concave minimization and error bounds, we study a convex-constrained penalized formulation for general CM problems. The advantage of such formulation is that it allows us to leverage non-convex optimization techniques, such as the simple projected gradient method, to build algorithms. We will explore the theory of this framework, particularly, conditions under which the formulation provides exact penalization results. We will also examine practical aspects, such as computational aspects and applications.

Bio:Wing-Kin (Ken) Ma is a Professor with the Department of Electronic Engineering, The Chinese University of Hong Kong. His research interests lie in signal processing, optimization and communications, with recent focus on structured matrix factorization and coarsely quantized MIMO transceiver designs. He has rich editorial experience; in particular, he was the Editor-in-Chief of IEEE Transactions on Signal Processing from 2021 to 2023. He is the recipient of several awards such as 2015 IEEE Signal Processing Magazine Best Paper Award and 2018 IEEE Signal Processing Society (SPS) Best Paper Award. He previously served as a Technical Committee Member of SPCOM-TC and SPTM-TC, as the SPS Regional 10 Director-at-Large (2020—2021), and as a Technical Program Co-Chair of ICASSP 2023; and was an IEEE SPS Distinguished Lecturer (2018—2019).