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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Vydáno v:International Conference on Signal Processing (Print) s. 1601 - 1604
Hlavní autoři: Junhui Qian, Zishu He, Yile Zhang, Bo Wu
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.11.2016
Témata:
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
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Abstract 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.
AbstractList 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.
Author Zishu He
Junhui Qian
Yile Zhang
Bo Wu
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  surname: Zishu He
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  email: zshe@uestc.edu.cn
  organization: Dept. of EE, Univ. of Electron. Sci. & Technol. of China, Chengdu, China
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  surname: Yile Zhang
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  email: zhyile163@163.com
  organization: Dept. of EE, Univ. of Electron. Sci. & Technol. of China, Chengdu, China
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  surname: Bo Wu
  fullname: Bo Wu
  email: rambowu11@gmail.com
  organization: Georgia Inst. of Technol., Atlanta, GA, USA
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Snippet 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...
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StartPage 1601
SubjectTerms 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
Title Null broadening adaptive beamforming based on semidefinite programming
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