Array spatial thinning for interference mitigation by semidefinite programming

We study the problem of interference mitigation in a phased array, where a subset containing k out of a total of N receivers creates a virtual spatial null for an incoming interference. The signal-of-interest and interference are represented by their corresponding steering vectors, and an optimum su...

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Bibliographic Details
Published in:2017 25th European Signal Processing Conference (EUSIPCO) pp. 2230 - 2234
Main Authors: Nosrati, Hamed, Aboutanios, Elias, Smith, David B.
Format: Conference Proceeding
Language:English
Published: EURASIP 01.08.2017
Subjects:
antenna selection
Array thinning
binary quadratic constrained programming
convex optimization
Correlation
Interference
Minimization
Optimization
Phased arrays
Programming
semidefinite programming
Signal processing algorithms
ISSN:2076-1465
Online Access:Get full text
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Summary:We study the problem of interference mitigation in a phased array, where a subset containing k out of a total of N receivers creates a virtual spatial null for an incoming interference. The signal-of-interest and interference are represented by their corresponding steering vectors, and an optimum subarray is chosen such that the two vectors are as orthogonal as possible. This optimization is a binary quadratic non-convex minimization. We propose a semidefinite programming method to find suboptimal solutions using an optimal randomized sampling strategy. We show that the proposed method provides solutions as good as an exhaustive search with a cubic computational complexity. Furthermore, the proposed algorithm outperforms existing methods by solving the problem in a higher dimensionality.
ISSN:2076-1465
DOI:10.23919/EUSIPCO.2017.8081606