Map2APS is a new large-scale benchmark with 2.55 million samples from 51 urban maps for predicting angle power spectra from geometry, featuring a cross-map split and MS-AReg baseline with 0.948 cosine similarity.
RadioUNet: Fast Ra- dio Map Estimation With Convolutional Neural Networks
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CITYMPC, a cVAE model, predicts full per-path multipath component parameters from POV images and height maps alone, matching ray-tracing accuracy with 1.29 dB power MAE and 7.25 ns delay MAE across 427k links in five cities while releasing the dataset as a benchmark.
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Map2APS: A Physically Grounded Benchmark for Direct Angle Power Spectrum Prediction from Urban Geometry
Map2APS is a new large-scale benchmark with 2.55 million samples from 51 urban maps for predicting angle power spectra from geometry, featuring a cross-map split and MS-AReg baseline with 0.948 cosine similarity.
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CITYMPC: A Large-Scale Physics-Informed Benchmark and Tool for Generative Complete Multipath Wireless Channel Modeling
CITYMPC, a cVAE model, predicts full per-path multipath component parameters from POV images and height maps alone, matching ray-tracing accuracy with 1.29 dB power MAE and 7.25 ns delay MAE across 427k links in five cities while releasing the dataset as a benchmark.