An algebraic approach to rank-constrained beamforming

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Abstract

This paper presents a new approach to solving the rank constrained beamforming problem. Instead of relaxing the problem to a feasible set of the positive semidefinite matrices, we restrict the problem to a space of polynomials whose dimension is equal to the desired rank. The solution to the resulting optimization is then required to be full rank, allowing a simple matrix decomposition to recover the beamforming matrix exactly. Simulation results show an exact agreement of the solution with the proposed algebraic structure, as well as significant performance benefits in terms of sidelobe suppression compared with previous methods.

Details

Original languageEnglish
Title of host publication2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
Publication statusPublished - 14 Jan 2016
MoE publication typeA4 Article in a conference publication
EventIEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing - Cancun, Mexico
Duration: 13 Dec 201516 Dec 2015
Conference number: 6
http://inspire.rutgers.edu/camsap2015/

Workshop

WorkshopIEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing
Abbreviated titleCAMSAP
CountryMexico
CityCancun
Period13/12/201516/12/2015
Internet address

    Research areas

  • Adaptive beamforming, convex optimization, polynomial ideals

ID: 1954464