This repository serves as a curated collection of outstanding papers and code related to learning-based radio maps (RM), also referred to as channel knowledge maps (CKM).
More information is in
A Tutorial on Learning-Based Radio Map Construction: Data, Paradigms, and Physics-Awarenes [Arxiv ]
If there are any of your papers that have not been collected, please contact us.
RadioUNet: Fast Radio Map Estimation With Convolutional Neural Networks [IEEE TWC 2021 ]
[Code ]
RME-GAN: A Learning Framework for Radio Map Estimation Based on Conditional Generative Adversarial Network [IEEE IoT J 2023 ]
[Code ]
RadioDiff: An Effective Generative Diffusion Model for Sampling-Free Dynamic Radio Map Construction [IEEE TCCN 2025 ]
[Code ]
RadioDiff- $k^2$ : Helmholtz Equation Informed Generative Diffusion Model for Multi-Path Aware Radio Map Construction [IEEE JSAC 2026 ]
[Code ]
RadioDiff-3D: A 3D× 3D Radio Map Dataset and Generative Diffusion-Based Benchmark for 6G Environment-Aware Communication [IEEE TNSE 2025 ]
[Code ]
Paying Deformable Attention to Sparse Spatial Observations for Deep Radio Map Estimation [IEEE TCCN 2025 ]
[Code ]
RadioMamba: Breaking the Accuracy-Efficiency Trade-Off in Radio Map Construction Via a Hybrid Mamba-UNet [IEEE TNSE 2025 ]
[Code ]
RadioGAT: A Joint Model-Based and Data-Driven Framework for Multi-Band Radiomap Reconstruction via Graph Attention Networks [IEEE TWC 2024 ]
[Code ]
ACT-GAN: Radio map construction based on generative adversarial networks with ACT blocks [IET communications 2024 ]
[Code ]
Real-Time Outdoor Localization Using Radio Maps: A Deep Learning Approach [IEEE TWC 2023 ]
[Code ]
Deep Completion Autoencoders for Radio Map Estimation [IEEE TWC 2022 ]
[Code ]
iRadioDiff: Physics Informed Diffusion Model for Effective Indoor Radio Map Construction and Localization [IEEE ICC 2026 ]
[Code ]
PhyRMDM: Physics-Informed Representation Alignment for Sparse Radio-Map Reconstruction [ACM MM BNI 2025 ]
[Code ]
SIP2Net: Situational-Aware Indoor Pathloss-Map Prediction Network for Radio Map Generation [IEEE ICASSP 2025 ]
[Code ]
OpenPathNet: An Open-Source RF Multipath Data Generator for AI-Driven Wireless Systems [IEEE VTC2026-Spring ]
[Code ]
TransPathNet: A Novel Two-Stage Framework for Indoor Radio Map Prediction [IEEE ICASSP 2025 ]
[Code ]
PMNet: Robust Pathloss Map Prediction via Supervised Learning [IEEE GlobeCom 2023 ]
[Code ]
RadioDiff-FS: Physics-Informed Manifold Alignment in Few-Shot Diffusion Models for High-Fidelity Radio Map Construction [Arxiv 2026 ]
[Code ]
U6G XL-MIMO Radiomap Prediction: Multi-Config Dataset and Beam Map Approach [Arxiv 2026 ]
[Code ]
PathFinder: Advancing Path Loss Prediction for Single-to-Multi-Transmitter Scenario [Arxiv 2025 ]
[Code ]
RF-3DGS: Wireless Channel Modeling with Radio Radiance Field and 3D Gaussian Splatting [ArXiv 2025 ]
[Code ]
RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Construction [IEEE TWC 2026 ]
CF-CGN: Channel Fingerprints Extrapolation for Multi-band Massive MIMO Transmission based on Cycle-Consistent Generative Networks [IEEE JSAC 2025 ]
A Disentangled Representation Learning Framework for Low-altitude Network Coverage Prediction [IEEE Transactions on Mobile Computing 2025 ]
Fast Transmission Control Adaptation for URLLC via Channel Knowledge Map and Meta-Learning [IEEE Internet of Things Journal 2025 ]
Radiation Source Localization Using Radio Maps: A Computer Vision Approach [IEEE Wireless Communications Letters 2025 ]
SC-GAN: A spectrum cartography with satellite Internet based on Pix2Pix generative adversarial network [China Communications 2025 ]
KAN Based Interpretable Radio Map Prediction Framework with Symbolic Data Fusion [IEEE Transactions on Cognitive Communications and Networking 2025 ]
Visual transformer based unified framework for radio map estimation and optimized site selection [IEICE Transactions on Communications 2025 ]
3D-RadioDiff: An Altitude-Conditioned Diffusion Model for 3D Radio Map Construction [IEEE Wireless Communications Letters 2025 ]
Radio map estimation using a CycleGAN-based learning framework for 6G wireless communication [Digital Communications and Networks 2025 ]
Constructing Frequency Modulation-Broadcasting Map Based on Semi-Supervised Clustering [IEEE Transactions on Broadcasting 2025 ]
Physics-Guided Language Model via Low-Rank Adaptation for Path Loss Prediction [IEEE Transactions on Cognitive Communications and Networking 2025 ]
Fast Transmission Control Adaptation for URLLC via Channel Knowledge Map and Meta-Learning [IEEE Communications Magazine 2025 ]
A Data-driven Transfer Learning Method for Indoor Radio Map Estimation [IEEE Transactions on Vehicular Technology 2025 ]
TiRE-GAN: Task-Incentivized Generative Learning for Radiomap Estimation [IEEE Wireless Communications Letters 2025 ]
Electromagnetic wave property inspired radio environment knowledge construction and artificial intelligence based verification for 6G digital twin channel [Frontiers of Information Technology & Electronic Engineering 2025 ]
GPRT: A Gaussian Process Regression-Based Radio Map Construction Method for Rugged Terrain [IEEE Internet of Things Journal 2025 ]
WirelessNet: An Efficient Radio Access Network Model Based on Heterogeneous Graph Neural Networks [IEEE Access 2025 ]
WiFi-Diffusion: Achieving Fine-Grained WiFi Radio Map Estimation with Ultra-Low Sampling Rate by Diffusion Models [IEEE JSAC 2025 ]
An I2I Inpainting Approach for Efficient Channel Knowledge Map Construction [IEEE TWC 2025 ]
Radio Map Prediction from Aerial Images and Application to Coverage Optimization [IEEE TWC 2025 ]
Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks [IEEE TCCN 2025 ]
Leveraging Transfer Learning for Radio Map Estimation via Mixture of Experts [IEEE TCCN 2025 ]
Generating CKM Using Others' Data: Cross-AP CKM Inference with Deep Learning [IEEE TVT 2025 ]
Channel Gain Map Construction Based on Subregional Learning and Prediction [IEEE TVT 2025 ]
Time-Variant Radio Map Reconstruction With Optimized Distributed Sensors in Dynamic Spectrum Environments [IEEE IoT J 2025 ]
A Data-and-Semantic Dual-Driven Intelligent Inference Framework for Simultaneously Spectrum Map Construction and Signal Source Localization [IEEE IoTJ 2025 ]
IMNet: Interference-Aware Channel Knowledge Map Construction and Localization [IEEE WCL 2025 ]
3D-RadioDiff: An Altitude-Conditioned Diffusion Model for 3D Radio Map Construction [IEEE WCL 2025 ]
Geo2ComMap: Deep Learning-Based MIMO Throughput Prediction Using Geographic Data [IEEE WCL 2025 ]
Two-Stage Radio Map Construction With Real Environments and Sparse Measurements [IEEE WCL 2025 ]
Physics-Informed Neural Networks for Path Loss Estimation by Solving Electromagnetic Integral Equations [IEEE TWC 2024 ]
A Scalable and Generalizable Pathloss Map Prediction [IEEE TWC 2024 ]
Overview on IEEE 802.11bf: WLAN Sensing [IEEE Communications Surveys & Tutoria 2024 ]
Intelligent reconstruction algorithm of electromagnetic map based on propagation model [Journal of Communications and Networks 2024 ]
A Novel Multimodal Fusion Sensing-Based Channel Prediction Method for UAV Communications [IEEE Internet of Things Journal 2024 ]
Development of a Conditional Generative Adversarial Network Model for Television Spectrum Radio Environment Mapping [IEEE Access 2024 ]
A Tutorial on Environment-Aware Communications via Channel Knowledge Map for 6G [IEEE Communications Surveys & Tutorials 2024 ]
Diffraction and Scattering Aware Radio Map and Environment Reconstruction Using Geometry Model-Assisted Deep Learning [IEEE Transactions on Wireless Communications 2024 ]
Machine Learning for Channel Quality Prediction: From Concept to Experimental Validation [IEEE Transactions on Wireless Communications 2024 ]
ACT-GAN: Radio map construction based on generative adversarial networks with ACT blocks [IET communications 2024 ]
Machine Learning for Channel Quality Prediction: From Concept to Experimental Validation [IEEE TWC 2024 ]
Weighted Ensembles for Adaptive Active Learning [IEEE TSP 2024 ]
Deep-Learning-Based Radio Map Reconstruction for V2X Communications [IEEE TVT 2024 ]
Channel Path Loss Prediction Using Satellite Images: A Deep Learning Approach [IEEE TMLCN 2024 ]
Deep Learning for Reduced Sampling Spatial 3-D REM Reconstruction [IEEE OJCOMS 2024 ]
A Secure Wireless Transmission Scheme: Reconstructing Spatial Radio Environment Map and Redirecting Electromagnetic Signal Propagation Path [IEEE OJCOMS 2025 ]
Convolutional neural networks for predicting the perceived density of large urban fabrics [Elsevier CEUS 2025 ]
A robust learning framework for spatial-temporal-spectral radio map prediction [Elsevier ESWA 2025 ]
Machine learning methods comparison for maritime wireless signal strength prediction [Elsevier JEngAppai 2025 ]
Vision Transformers for Efficient Indoor Pathloss Radio Map Prediction [MDPI Electronics 2025 ]
DeepRT: A Hybrid Framework Combining Large Model Architectures and Ray Tracing Principles for 6G Digital Twin Channels [MDPI Electronics 2025 ]
Deep Learning-Empowered RF Sensing in Outdoor Environments: Recent Advances, Challenges, and Future Directions [MDPI Electronics 2024 ]
Machine-Learning-Based Path Loss Prediction for Vehicle-to-Vehicle Communication in Highway Environments [MDPI Applied Science 2025 ]
Reconstruction of Radio Environment Map Based on Multi-Source Domain Adaptive of Graph Neural Network for Regression [MDPI Sensors 2025 ]
Electromagnetic wave property inspired radio environment knowledge construction and artificial intelligence based verification for 6G digital twin channel [Springer FITEE 2025 ]
REM-U-Net: Deep Learning Based Agile REM Prediction With Energy-Efficient Cell-Free Use Case [IEEE OJSP 2024 ]
Rigorous Indoor Wireless Communication System Simulations With Deep Learning-Based Radio Propagation Models [IEEE JMMCT 2024 ]
A Deep-Learning Approach to a Volumetric Radio Environment Map Construction for UAV-Assisted Networks [Wiley IJAP 2024 ]
Super-Resolution of Wireless Channel Characteristics: A Multitask Learning Model [IEEE TAP 2023 ]
Cell-Level RSRP Estimation With the Image-to-Image Wireless Propagation Model Based on Measured Data [IEEE TCCN 2023 ]
Accurate Spectrum Map Construction for Spectrum Management Through Intelligent Frequency-Spatial Reasoning [IEEE TCOMM 2023 ]
A Graph Neural Network Based Radio Map Construction Method for Urban Environment [IEEE WLC 2023 ]
A Deep Learning-Based Indoor Radio Estimation Method Driven by 2.4 GHz Ray-Tracing Data [IEEE Access,2023 ]
A FL-Based Radio Map Reconstruction Approach for UAV-Aided Wireless Networks [MDPI electronics,2023 ]
Multi-Stage RF Emitter Search and Geolocation With UAV: A Cognitive Learning-Based Method [IEEE Transactions on Vehicular Technology 2023 ]
DeepREM: Deep-Learning-Based Radio Environment Map Estimation From Sparse Measurements [IEEE Access 2023 ]
RME-GAN: A Learning Framework for Radio Map Estimation Based on Conditional Generative Adversarial Network [IEEE Internet of Things Journal 2023 ]
A Deep Learning-Based Indoor Radio Estimation Method Driven by 2.4 GHz Ray-Tracing Data [IEEE Access 2023 ]
Temporal prediction for spectrum environment maps with moving radiation sources [IET Communication 2023 ]
Machine Learning-Based Urban Canyon Path Loss Prediction Using 28 GHz Manhattan Measurements [IEEE TAP 2022 ]
Pseudo Ray-Tracing: Deep Leaning Assisted Outdoor mm-Wave Path Loss Prediction [IEEE WLC 2022 ]
Fast Radio Propagation Prediction with Deep Learning [Compressed Sensing in Information Processing 2022 ]
An Overview of Propagation Models BasElectriacaled on Deep Learning Techniques [International Journal Electrical Engineering 2022 ]
An Empirical Study on Using CNNs for Fast Radio Signal Prediction [Springer SN Computer Science 2022 ]
Machine Learning-Based Radio Coverage Prediction in Urban Environments [IEEE TNSE 2020 ]
Radiomap Inpainting for Restricted Areas Based on Propagation Priority and Depth Map [IEEE TNSE 2020 ]
RadioDiff-Turbo: Lightweight Generative Large Electromagnetic Model for Wireless Digital Twin Construction [IEEE INFOCOM wksp 2025 ]
Radio Map Reconstruction Based on Nas Enhanced Deep Regularization Completion for Uav Communications [2025 VTC2025-Spring ]
DULRTC-RME: A Deep Unrolled Low-rank Tensor Completion Network for Radio Map Estimation [2025 ICASSP ]
FedRME: Importance-Aware Cooperative Radio Map Estimation Empowered by Vertical Federated Learning [2025 ICC Workshops ]
A Diffusion-Based Propagation Model for Path Loss Prediction in Indoor Environments [2025 EuCAP ]
RadioDiff-Turbo: Lightweight Generative Large Electromagnetic Model for Wireless Digital Twin Construction （UNIC） [2025 IEEE INFOCOM WKSHPS ]
UNet-Based Deep Learning Pathloss Estimator with Boundary Condition Input [2025 RWS ]
Learning Blockage and Reflection Geometry for MIMO Beam Map Construction [ICC 2025 - IEEE International Conference on Communications ]
Environment-Aware AoD and AoA Prediction for Wireless Networks Utilizing Machine Learning [2025 ICAIIC ]
Channel-Aware Deep Learning for Superimposed Pilot Power Allocation and Receiver Design [2025 VTC2025-Spring ]
Ultra-Grained Channel Fingerprint Construction via Conditional Generative Diffusion Models [IEEE INFOCOM 2025 ]
Radio Map Estimation via Latent-Domain Plug-and-Play Denoisers [IEEE ICASSP 2025 ]
IPP-Net: A Generalizable Deep Neural Network Model for Indoor Pathloss Radio Map Prediction [IEEE ICASSP 2025 ]
Spatial Transformers for Radio Map Estimation [IEEE ICC 2025 ]
Generative CKM construction using partially observed data with diffusion model [IEEE VTC-Spring 2025 ]
Deep Learning-Based CKM Construction with Image Super-Resolution [IEEE VTC-Spring 2025 ]
Data-and-Semantic Dual-Driven Spectrum Map Construction for 6G Spectrum Management [IEEE GlobeCom 2024 ]
Channel Knowledge Map Construction with Laplacian Pyramid Reconstruction Network [IEEE WCNC 2024 ]
Machine Learning-based Predictive Channel Modeling for 6G Wireless Communications Using Image Semantic Segmentation [IEEE PIMRC 2024 ]
Radio Map Estimation with Deep Dual Path Autoencoders and Skip Connection Learning [IEEE PIMRC 2024 ]
FedRME: Federated Learning for Enhanced Distributed Radiomap Estimation [IEEE VTC-Fall 2024 ]
Channel Knowledge Maps Construction Based on Point Cloud Environment Information [IEEE VTC-Fall 2024 ]
A Transformer-Based Network for Unifying Radio Map Estimation and Optimized Site Selection [2024 ICASSPW ]
Fine Tuning an AI-Based Indoor Radio Propagation Model with Crowd-Sourced Data [2024 EuCAP ]
Distributed Radio Map Reconstruction Based on Semi-Asynchronous Federated Learning Generative Adversarial Networks [2024 ICCC Workshops ]
RobUNet: A Radio Map Construction Method with A Strong Generalization Capability [2024 IEEE Global Communications Conference ]
A 2D Deep Residual Learning Approach for 3D Indoor Radio Map Estimation [ICC 2024 - IEEE International Conference on Communications ]
Towards the Metaverse: Distributed Radio Map Reconstruction based on Federated Learning Generative Adversarial Networks [2024 IWCMC ]
Optimal Base Station Sleep Control via Multi-Agent Reinforcement Learning with Data-Driven Radio Environment Map Calibration [2024 VTC2024-Spring ]
A Bayesian Learning Approach to Wireless Outdoor Heatmap Construction Using Deep Gaussian Process [2024 58th Asilomar Conference on Signals, Systems, and Computers ]
A New Approach to Predict Radio Map via Learning-Based Spatial Loss Field [2024 ICASSPW ]
RecuGAN: A Novel Generative AI Approach for Synthesizing RF Coverage Maps [2024 ICCCN ]
Radio Map Reconstruction Based on Transformer from Sparse Measurement [2024 ICCT ]
Deep Learning-Based Radio Estimation Using a Semi-Automatically Created Indoor Building Information [2024 WCNC ]
Evaluation of Transformer Empowered Channel Prediction for 5G and Beyond Communication [2024 VTC2024-Fall ]
Radio Map Estimation (RME) with Deep Progressive Network [2024 MIPR ]
Fast Indoor Radio Propagation Prediction using Deep Learning [2024 EuCAP ]
Deep Machine Learning-Based AoD Map and AoA Map Construction for Wireless Networks [2024 VTC2024-Spring ]
RM-Gen: Conditional Diffusion Model-Based Radio Map Generation for Wireless Networks [IEEE IFIP Networking 2024 ]
Data-Driven Radio Environment Map Estimation Using Graph Neural Networks [IEEE ICC wksp 2024 ]
Fast and Accurate Cooperative Radio Map Estimation Enabled by GAN [IEEE ICC wksp 2024 ]
A Transformer-Based Network for Unifying Radio Map Estimation and Optimized Site Selection [IEEE ICASSP wksp 2024 ]
Radio DIP - Completing Radio Maps using Deep Image Prior [IEEE GlobeCom 2023 ]
Deep Learning-Based Path Loss Prediction for Outdoor Wireless Communication Systems [IEEE ICASSP 2023 ]
Agile Radio Map Prediction Using Deep Learning [IEEE ICASSP 2023 ]
Transformer-Based Neural Surrogate for Link-Level Path Loss Prediction from Variable-Sized Maps [IEEE GlobeCom 2023 ]
IRGAN: cGAN-based Indoor Radio Map Prediction [IEEE IFIP Networking 2023 ]
IndoorRSSINet - Deep learning based 2D RSSI map prediction for indoor environments with application to wireless localization
[IEEE COMSNETS 2023 ]
UnetRay: A Prediction Method of Indoor Radio Signal Strength Distribution [IEEE ICAIT 2023 ]
Locswinunet: A Neural Network for Urban Wireless Localization Using TOA and RSS Radio Maps [2023 MLSP ]
Three-Dimensional Radio Spectrum Map Prediction Based on Fully Connected Neural Network [2023 ICAIT ]
Federated Learning-Based Radio Environment Map Construction for Wireless Networks [2023 IEEE Global Communications Conference ]
Propagation Graph Representation Learning and Its Implementation in Direct Path Representation [2023 WCNC ]
UAV-aided Joint Radio Map and 3D Environment Reconstruction using Deep Learning Approaches [IEEE ICC 2022 ]
A Multi-Task Learning Model for Super Resolution of Wireless Channel Characteristics [IEEE GlobeCom 2022 ]
Deep Transfer Learning Based Radio Map Estimation for Indoor Wireless Communications [IEEE SPAWC 2022 ]
LocUNet: Fast Urban Positioning Using Radio Maps and Deep Learning [2022 ICASSP ]
Deep Transfer Learning Based Radio Map Estimation for Indoor Wireless Communications [2022 SPAWC ]
Learning Graph Convolutional Neural Networks to Predict Radio Environment Maps [2022 WPMC ]
RadioResUNet: Wireless Measurement by Deep Learning for Indoor Environments [2022 WPMC ]
Extending Machine Learning Based RF Coverage Predictions to 3D [2022 AP-S/URSI ]
Exemplar-Based Radio Map Reconstruction of Missing Areas Using Propagation Priority [2022 IEEE Global Communications Conference ]
Spatial Prediction of Channel Signal Strength Map Using Deep Fully Convolutional Neural Network [2022 56th Asilomar Conference on Signals, Systems, and Computers ]
Transformer based Radio Map Prediction Model for Dense Urban Environments [IEEE ISAPE 2021 ]
Radio Map Estimation Using a Generative Adversarial Network and Related Business Aspects [IEEE WPMC 2021 ]
Prediction of Indoor Wireless Coverage from 3D Floor Plans Using Deep Convolutional Neural Networks [IEEE LCN 2021 ]
GenMetaLoc: Learning to Learn Environment-Aware Fingerprint Generation for Sample Efficient Wireless Localization [ArXiv 2025 ]
Fusion of Pervasive RF Data with Spatial Images via Vision Transformers for Enhanced Mapping in Smart Cities [ArXiv 2025 ]
BS-1-to-N: Diffusion-Based Environment-Aware Cross-BS Channel Knowledge Map Generation for Cell-Free Networks [ArXiv 2025 ]
Channel Fingerprint Construction for Massive MIMO: A Deep Conditional Generative Approach [ArXiv 2025 ]
PINN and GNN-based RF Map Construction for Wireless Communication Systems [ArXiv 2025 ]
RMTransformer: Accurate Radio Map Construction and Coverage Prediction [ArXiv 2025 ]
LLM4MG: Adapting Large Language Model for Multipath Generation via Synesthesia of Machines [ArXiv 2025 ]
Machine Learning based Radio Environment Map Estimation for Indoor Visible Light Communication [ArXiv 2025 ]
Bayesian Radio Map Estimation: Fundamentals and Implementation via Diffusion Models [ArXiv 2025 ]
RadioDUN: A Physics-Inspired Deep Unfolding Network for Radio Map Estimation [ArXiv 2025 ]
RadioFormer: A Multiple-Granularity Radio Map Estimation Transformer with 1\textpertenthousand Spatial Sampling [ArXiv 2025 ]
RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimation [Arxiv 2025 ]
Temporal Spectrum Cartography in Low-Altitude Economy Networks: A Generative AI Framework with Multi-Agent Learning [ArXiv 2025 ]
ExposNet: A Deep Learning Framework for EMF Exposure Prediction in Complex Urban Environments [ArXiv 2025 ]
GenMetaLoc: Learning to Learn Environment-Aware Fingerprint Generation for Sample Efficient Wireless Localization [ArXiv 2025 ]
FERMI: Flexible Radio Mapping with a Hybrid Propagation Model and Scalable Autonomous Data Collection [ArXiv 2024 ]
Solving Maxwell's equations with Non-Trainable Graph Neural Network Message Passing [ArXiv 2024 ]
Radio Map Estimation -- An Open Dataset with Directive Transmitter Antennas and Initial Experiments [ArXiv 2024 ]
A Deep Unfolding-Based Scalarization Approach for Power Control in D2D Networks [ArXiv 2024 ]
Simulating, Fast and Slow: Learning Policies for Black-Box Optimization [ArXiv 2024 ]
White Paper on Radio Channel Modeling and Prediction to Support Future Environment-aware Wireless Communication Systems [ArXiv 2023 ]
Deep Learning Based Active Spatial Channel Gain Prediction Using a Swarm of Unmanned Aerial Vehicles [ArXiv 2023 ]
RadioNet: Transformer based Radio Map Prediction Model For Dense Urban Environments [ArXiv 2021 ]