A cross-fused generative beamforming method decouples 2D UPA channel sensing and uses bidirectional cross-attention plus conditional normalizing flows to generate high-gain beam candidates, reporting up to 83.6% normalized gain improvement with 93.8% less overhead in DeepMIMO simulations.
Explainable autoencoder design for RSSI-based multi-user beam probing and hybrid precoding,
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Generative Site-Specific Beamforming for UPAs via Decoupled Channel Sensing
A cross-fused generative beamforming method decouples 2D UPA channel sensing and uses bidirectional cross-attention plus conditional normalizing flows to generate high-gain beam candidates, reporting up to 83.6% normalized gain improvement with 93.8% less overhead in DeepMIMO simulations.