101. Sparse Array Quiescent Beamformer Design Combining Adaptive and Deterministic Constraints
- Author
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Xianghua Wang, Xianbin Cao, Xiangrong Wang, and Moeness G. Amin
- Subjects
Beamforming ,Mathematical optimization ,010401 analytical chemistry ,020206 networking & telecommunications ,Data_CODINGANDINFORMATIONTHEORY ,02 engineering and technology ,01 natural sciences ,0104 chemical sciences ,Linear-fractional programming ,Signal-to-noise ratio ,Sparse array ,Sensor array ,0202 electrical engineering, electronic engineering, information engineering ,Array data structure ,Electrical and Electronic Engineering ,Antenna (radio) ,Adaptive beamformer ,Computer Science::Information Theory ,Mathematics - Abstract
In this paper, we examine sparse array quiescent beamforming for multiple sources in interference-free environment. To maximize the output signal-to-noise ratio (SNR), the beamformer design comprises two intertwined stages, the determination of beamforming weights and the reconfiguration of array structure. The SNR maximization may produce high sidelobe levels, making the receiver vulnerable to interferences. We consider the problem of achieving maximum SNR beamforming subject to specified quiescent pattern constraints and, as such, combine both adaptive and deterministic approaches for sparse array configurations. We employ two convex relaxation methods and an iterative linear fractional programming algorithm to solve the nonconvex antenna selection problem for sparse array beamformers. Simulation examples demonstrate that the array configuration plays a vital role in determining the beamforming performance in interference-free scenarios.
- Published
- 2017
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