An iterative approach to nonconvex QCQP with applications in signal processing
2016 (English)In: Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, IEEE, 2016Conference paper (Refereed)
This paper introduces a new iterative approach to solve or to approximate the solutions of the nonconvex quadratically constrained quadratic programs (QCQP). First, this constrained problem is transformed to an unconstrained problem using a specialized penalty-based method. A tight upper-bound for the alternative unconstrained objective is introduced. Then an efficient minimization approach to the alternative unconstrained objective is proposed and further studied. The proposed approach involves power iterations and minimization of a convex scalar function in each iteration, which are computationally fast. The important design problem of multigroup multicast beamforming is formulated as a nonconvex QCQP and solved using the proposed method.
Place, publisher, year, edition, pages
Constraint theory, Iterative methods, Quadratic programming, Constrained problem, Design problems, Iterative approach, Multi-group, Quadratically-constrained quadratic programs, Scalar function, Unconstrained problems, Upper Bound, Signal processing
IdentifiersURN: urn:nbn:se:kth:diva-202884DOI: 10.1109/SAM.2016.7569622ScopusID: 2-s2.0-84990829369ISBN: 9781509021031 OAI: oai:DiVA.org:kth-202884DiVA: diva2:1080484
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016, 10 July 2016 through 13 July 2016
QC 201703102017-03-102017-03-102017-03-10Bibliographically approved