CNN learns sparse array designs for single-source single-interferer beamforming via pre-steering, reporting over 90% test accuracy across angles.
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A CNN and ResNet50 classifier selects among 56 angular-sector-based sparse array configurations to achieve near-optimal SINR in adaptive beamforming with low performance deviation.
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Deep Learning Based Sparse Array Design with Pre-Steering for Adaptive Beamforming
CNN learns sparse array designs for single-source single-interferer beamforming via pre-steering, reporting over 90% test accuracy across angles.
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Angular Sector-Based Sparse Array Design for Adaptive Beamforming Using Deep Learning
A CNN and ResNet50 classifier selects among 56 angular-sector-based sparse array configurations to achieve near-optimal SINR in adaptive beamforming with low performance deviation.