A Tutorial on Learning-Based Radio Map Construction: Data, Paradigms, and Physics-Awareness
eess.SY, cs.SY, eess.SP
Submitted: 2026-03-18
Updated: 2026-09-27
Code: https://github.com/UNIC-Lab/Awesome-Radio-Map-Categorized
Terminology
Sources
- White Paper on Radio Channel Modeling and Prediction to Support Future Environment-aware Wireless Communication Systems
- Road to 6G Digital Twin Networks: Multi-Task Adaptive Ray-Tracing as a Key Enabler
- RadioFormer: A Multiple-Granularity Radio Map Estimation Transformer with 1\textpertenthousand Spatial Sampling
- BS-1-to-N: Diffusion-Based Environment-Aware Cross-BS Channel Knowledge Map Generation for Cell-Free Networks
- Neural Gaussian Radio Fields for Channel Estimation
- 6D Channel Knowledge Map Construction via Bidirectional Wireless Gaussian Splatting
- BeamCKMDiff: Beam-Aware Channel Knowledge Map Construction via Diffusion Transformer
- RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimation
- Bayesian Radio Map Estimation: Fundamentals and Implementation via Diffusion Models
- Solving Maxwell's equations with Non-Trainable Graph Neural Network Message Passing
- BeamCKM: A Framework of Channel Knowledge Map Construction for Multi-Antenna Systems
- RadioGen3D: 3D Radio Map Generation via Adversarial Learning on Large-Scale Synthetic Data
- WAIR-D: Wireless AI Research Dataset
- DeepMIMO: A Generic Deep Learning Dataset for Millimeter Wave and Massive MIMO Applications
- Deep Learning Based Active Spatial Channel Gain Prediction Using a Swarm of Unmanned Aerial Vehicles
- Fusion of Pervasive RF Data with Spatial Images via Vision Transformers for Enhanced Mapping in Smart Cities
- RadioFlow: Efficient Radio Map Construction Framework with Flow Matching
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