PR-HBFNet combines a Transformer encoder for per-element pattern selection with model-driven residual learning for analog-digital precoding in RPA-equipped HAPS MIMO, approaching greedy spectral efficiency at lower complexity.
Iterative Algorithm Induced Deep-Unfolding Neural Networks: Precoding Design for Mul- tiuser MIMO Systems,
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Transformer-Based Hybrid Beamforming with Reconfigurable Pixel Antenna for HAPS Communications
PR-HBFNet combines a Transformer encoder for per-element pattern selection with model-driven residual learning for analog-digital precoding in RPA-equipped HAPS MIMO, approaching greedy spectral efficiency at lower complexity.