Null broadening adaptive beamforming based on semidefinite programming

In this paper, we introduce a procedure for the null broadening algorithm design with respect to the perturbation of the interference location. This method is based on maximizing the array output signal-to-interference-plus-noise-ratio (SINR) subject to quadratic constraints. The design problem can...

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Bibliographic Details
Published in:International Conference on Signal Processing (Print) pp. 1601 - 1604
Main Authors: Junhui Qian, Zishu He, Yile Zhang, Bo Wu
Format: Conference Proceeding
Language:English
Published: IEEE 01.11.2016
Subjects:
Adaptive arrays
Array signal processing
beampattern shaping constraints
Interference
Optimization
Programming
quadratically constrained quadratic programming
Robust adaptive beamforming
Robustness
semidefinite programming
Signal to noise ratio
ISBN:9781509013449, 150901344X
ISSN:2164-5221
Online Access:Get full text
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Summary:In this paper, we introduce a procedure for the null broadening algorithm design with respect to the perturbation of the interference location. This method is based on maximizing the array output signal-to-interference-plus-noise-ratio (SINR) subject to quadratic constraints. The design problem can be cast as a fractional quadratically constrained quadratic programming (QCQP) problem that can be solved efficiently using the semidefinite programming (SDP) techniques, the semidefinite relaxation can be used to obtain a lower bound on the optimal objective function. This proposed approach imposes broadened nulls towards the interference region while possesses well-maintained pattern. Theoretical analysis and numerical results demonstrate that the performance of proposed adaptive beamformer is almost always close to optimal.
ISBN:9781509013449
150901344X
ISSN:2164-5221
DOI:10.1109/ICSP.2016.7878097