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Zhi-Quan Luo

Researcher at The Chinese University of Hong Kong

Publications -  482
Citations -  38350

Zhi-Quan Luo is an academic researcher from The Chinese University of Hong Kong. The author has contributed to research in topics: Convex optimization & Beamforming. The author has an hindex of 86, co-authored 464 publications receiving 34268 citations. Previous affiliations of Zhi-Quan Luo include North Carolina State University & Huawei.

Papers
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Journal ArticleDOI

Semidefinite Relaxation of Quadratic Optimization Problems

TL;DR: This article has provided general, comprehensive coverage of the SDR technique, from its practical deployments and scope of applicability to key theoretical results, and showcased several representative applications, namely MIMO detection, B¿ shimming in MRI, and sensor network localization.
Book

Mathematical Programs with Equilibrium Constraints

TL;DR: Results in the book are expected to have significant impacts in such disciplines as engineering design, economics and game equilibria, and transportation planning, within all of which MPEC has a central role to play in the modelling of many practical problems.
Journal ArticleDOI

Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem

TL;DR: A new approach to robust adaptive beamforming in the presence of an arbitrary unknown signal steering vector mismatch is developed based on the optimization of worst-case performance.
Journal ArticleDOI

Transmit beamforming for physical-layer multicasting

TL;DR: This paper considers the problem of downlink transmit beamforming for wireless transmission and downstream precoding for digital subscriber wireline transmission, in the context of common information broadcasting or multicasting applications wherein channel state information (CSI) is available at the transmitter.
Proceedings ArticleDOI

An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel

TL;DR: This paper proposes a linear transceiver design algorithm for weighted sum-rate maximization that is based on iterative minimization of weighted mean squared error (MSE) and extends the algorithm to a general class of utility functions and establishes its convergence.