A method to construct propagation-consistent wireless environment digital twins from sparse CSI by creating a geometry-prior Bayesian channel map and calibrating a scene-level EM property field via differentiable ray tracing.
Nerf2: Neural radio-frequency radiance fields,
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
verdicts
UNVERDICTED 4representative citing papers
RadTwin conditions a neural radio-propagation model on scene point clouds via physics-informed sparse attention, achieving 0.846 SSIM and 0.023 LPIPS on dynamic indoor scenes without retraining.
A new site-specific model uses 3D geometry maps and recursive UTD diffraction calculations to predict urban radio path loss and time-varying Doppler more accurately than 3GPP models, with RMSE reductions of 7.1 dB in complex NLOS cases.
GAI-NeRF combines geometric algebra attention and an adaptive ray tracing module inside a NeRF model to deliver more accurate and generalizable wireless channel predictions across varied indoor environments.
citing papers explorer
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Propagation-Consistent Wireless Environment Digital Twin Construction Under Sparse Measurements
A method to construct propagation-consistent wireless environment digital twins from sparse CSI by creating a geometry-prior Bayesian channel map and calibrating a scene-level EM property field via differentiable ray tracing.
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RadTwin: Generalizable Wireless Digital Twin for Dynamic Environments
RadTwin conditions a neural radio-propagation model on scene point clouds via physics-informed sparse attention, achieving 0.846 SSIM and 0.023 LPIPS on dynamic indoor scenes without retraining.
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A Geometry Map-Based Site-Specific Propagation Channel Model for Urban Scenarios
A new site-specific model uses 3D geometry maps and recursive UTD diffraction calculations to predict urban radio path loss and time-varying Doppler more accurately than 3GPP models, with RMSE reductions of 7.1 dB in complex NLOS cases.
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A Geometric Algebra-informed NeRF Framework for Generalizable Wireless Channel Prediction
GAI-NeRF combines geometric algebra attention and an adaptive ray tracing module inside a NeRF model to deliver more accurate and generalizable wireless channel predictions across varied indoor environments.