A neural surrogate using surface-attached photons and spherical splatting predicts channel impulse responses in milliseconds, generalizing to new transmitter positions and antenna patterns after training on ray-traced data.
Toward physics-based generalizable convolutional neural network models for indoor propagation,
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Photon Splatting: A Physics-Guided Neural Surrogate for Real-Time Wireless Channel Prediction
A neural surrogate using surface-attached photons and spherical splatting predicts channel impulse responses in milliseconds, generalizing to new transmitter positions and antenna patterns after training on ray-traced data.