Title
Randomized Algorithms for Optimal Solutions of Double-Sided QCQP With Applications in Signal Processing
Abstract
Quadratically constrained quadratic programming (QCQP) with double-sided constraints has plenty of applications in signal processing as have been addressed in recent years. QCQP problems are hard to solve, in general, and they are typically approached by solving a semidefinite programming (SDP) relaxation followed by a postprocessing procedure. Existing postprocessing schemes include Gaussian randomization to generate an approximate solution, rank reduction procedure (the so-called purification), and some specific rank-one matrix decomposition techniques to yield a globally optimal solution. In this paper, we propose several randomized postprocessing methods to output not an approximate solution but a globally optimal solution for some solvable instances of the double-sided QCQP (i.e., instances with a small number of constraints). We illustrate their applicability in robust receive beamforming, radar optimal code design, and broadcast beamforming for multiuser communications. As a byproduct, we derive an alternative (shorter) proof for the Sturm-Zhang rank-one matrix decomposition theorem.
Year
DOI
Venue
2014
10.1109/TSP.2013.2297683
IEEE Transactions on Signal Processing
Keywords
Field
DocType
signal processing,gaussian processes,quadratic programming,semidefinite programming (sdp) relaxation,multicast downlink beamforming,optimal solutions,matrix algebra,robust receive beamforming,signal processing applications,homogeneous quadratically constrained quadratic program (qcqp),semidefinite programming,gaussian randomization,double sided qcqp,sturm-zhang rank-one matrix decomposition theorem,randomized algorithms,sdp,optimal radar waveform,quadratically constrained quadratic programming,radar,robustness,vectors,interference
Second-order cone programming,Signal processing,Randomized algorithm,Beamforming,Mathematical optimization,Quadratically constrained quadratic program,Matrix decomposition,Quadratic programming,Semidefinite programming,Mathematics
Journal
Volume
Issue
ISSN
62
5
1053-587X
Citations 
PageRank 
References 
23
0.89
28
Authors
2
Name
Order
Citations
PageRank
Yongwei Huang181450.83
Daniel Pérez Palomar22146134.10