R²Net applies 2D deep residual learning with height embedding to estimate 3D radio maps, offering separate indoor and outdoor variants plus a new 3D indoor dataset.
Sparse Bayesian learning-based hierarchical cons truction for 3D radio environment maps incorporating channel shadowing ,
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R$^{2}$Net: 2D Deep Residual Learning with Height Embedding for 3D Radio Map Estimation
R²Net applies 2D deep residual learning with height embedding to estimate 3D radio maps, offering separate indoor and outdoor variants plus a new 3D indoor dataset.