Paper with Code

Journal

RadioUNet: Fast Radio Map Estimation With Convolutional Neural Networks

RME-GAN: A Learning Framework for Radio Map Estimation Based on Conditional Generative Adversarial Network

RadioDiff: An Effective Generative Diffusion Model for Sampling-Free Dynamic Radio Map Construction

RadioDiff-3D: A 3D× 3D Radio Map Dataset and Generative Diffusion-Based Benchmark for 6G Environment-Aware Communication

Paying Deformable Attention to Sparse Spatial Observations for Deep Radio Map Estimation

RadioMamba: Breaking the Accuracy-Efficiency Trade-Off in Radio Map Construction Via a Hybrid Mamba-UNet

ACT-GAN: Radio map construction based on generative adversarial networks with ACT blocks

Real-Time Outdoor Localization Using Radio Maps: A Deep Learning Approach

Deep Completion Autoencoders for Radio Map Estimation

Conference

PhyRMDM: Physics-Informed Representation Alignment for Sparse Radio-Map Reconstruction

SIP2Net: Situational-Aware Indoor Pathloss-Map Prediction Network for Radio Map Generation

TransPathNet: A Novel Two-Stage Framework for Indoor Radio Map Prediction

PMNet: Robust Pathloss Map Prediction via Supervised Learning

ArXiv

RF-3DGS: Wireless Channel Modeling with Radio Radiance Field and 3D Gaussian Splatting

RadioDiff-$k^2$ : Helmholtz Equation Informed Generative Diffusion Model for Multi-Path Aware Radio Map Construction

Paper without Code

Journal

CF-CGN: Channel Fingerprints Extrapolation for Multi-band Massive MIMO Transmission based on Cycle-Consistent Generative Networks

Fast Transmission Control Adaptation for URLLC via Channel Knowledge Map and Meta-Learning

Radiation Source Localization Using Radio Maps: A Computer Vision Approach

SC-GAN: A spectrum cartography with satellite Internet based on Pix2Pix generative adversarial network

KAN Based Interpretable Radio Map Prediction Framework with Symbolic Data Fusion

Visual transformer based unified framework for radio map estimation and optimized site selection

3D-RadioDiff: An Altitude-Conditioned Diffusion Model for 3D Radio Map Construction

Radio map estimation using a CycleGAN-based learning framework for 6G wireless communication

Constructing Frequency Modulation-Broadcasting Map Based on Semi-Supervised Clustering

Physics-Guided Language Model via Low-Rank Adaptation for Path Loss Prediction

Fast Transmission Control Adaptation for URLLC via Channel Knowledge Map and Meta-Learning

A Data-driven Transfer Learning Method for Indoor Radio Map Estimation

TiRE-GAN: Task-Incentivized Generative Learning for Radiomap Estimation

Electromagnetic wave property inspired radio environment knowledge construction and artificial intelligence based verification for 6G digital twin channel

GPRT: A Gaussian Process Regression-Based Radio Map Construction Method for Rugged Terrain

WirelessNet: An Efficient Radio Access Network Model Based on Heterogeneous Graph Neural Networks

WiFi-Diffusion: Achieving Fine-Grained WiFi Radio Map Estimation with Ultra-Low Sampling Rate by Diffusion Models

An I2I Inpainting Approach for Efficient Channel Knowledge Map Construction

Radio Map Prediction from Aerial Images and Application to Coverage Optimization

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks

Leveraging Transfer Learning for Radio Map Estimation via Mixture of Experts

Generating CKM Using Others' Data: Cross-AP CKM Inference with Deep Learning

Channel Gain Map Construction Based on Subregional Learning and Prediction

Time-Variant Radio Map Reconstruction With Optimized Distributed Sensors in Dynamic Spectrum Environments

A Data-and-Semantic Dual-Driven Intelligent Inference Framework for Simultaneously Spectrum Map Construction and Signal Source Localization

IMNet: Interference-Aware Channel Knowledge Map Construction and Localization

3D-RadioDiff: An Altitude-Conditioned Diffusion Model for 3D Radio Map Construction

Geo2ComMap: Deep Learning-Based MIMO Throughput Prediction Using Geographic Data

Two-Stage Radio Map Construction With Real Environments and Sparse Measurements

Physics-Informed Neural Networks for Path Loss Estimation by Solving Electromagnetic Integral Equations

A Scalable and Generalizable Pathloss Map Prediction

Overview on IEEE 802.11bf: WLAN Sensing

Intelligent reconstruction algorithm of electromagnetic map based on propagation model

A Novel Multimodal Fusion Sensing-Based Channel Prediction Method for UAV Communications

Development of a Conditional Generative Adversarial Network Model for Television Spectrum Radio Environment Mapping

A Tutorial on Environment-Aware Communications via Channel Knowledge Map for 6G

Diffraction and Scattering Aware Radio Map and Environment Reconstruction Using Geometry Model-Assisted Deep Learning

Machine Learning for Channel Quality Prediction: From Concept to Experimental Validation

RadioGAT: A Joint Model-Based and Data-Driven Framework for Multi-Band Radiomap Reconstruction via Graph Attention Networks

ACT-GAN: Radio map construction based on generative adversarial networks with ACT blocks

RadioGAT: A Joint Model-Based and Data-Driven Framework for Multi-Band Radiomap Reconstruction via Graph Attention Networks

Machine Learning for Channel Quality Prediction: From Concept to Experimental Validation

Weighted Ensembles for Adaptive Active Learning

Deep-Learning-Based Radio Map Reconstruction for V2X Communications

Channel Path Loss Prediction Using Satellite Images: A Deep Learning Approach

Deep Learning for Reduced Sampling Spatial 3-D REM Reconstruction

A Secure Wireless Transmission Scheme: Reconstructing Spatial Radio Environment Map and Redirecting Electromagnetic Signal Propagation Path

Convolutional neural networks for predicting the perceived density of large urban fabrics

A robust learning framework for spatial-temporal-spectral radio map prediction

Machine learning methods comparison for maritime wireless signal strength prediction

Vision Transformers for Efficient Indoor Pathloss Radio Map Prediction

DeepRT: A Hybrid Framework Combining Large Model Architectures and Ray Tracing Principles for 6G Digital Twin Channels

Deep Learning-Empowered RF Sensing in Outdoor Environments: Recent Advances, Challenges, and Future Directions

Machine-Learning-Based Path Loss Prediction for Vehicle-to-Vehicle Communication in Highway Environments

Reconstruction of Radio Environment Map Based on Multi-Source Domain Adaptive of Graph Neural Network for Regression

Electromagnetic wave property inspired radio environment knowledge construction and artificial intelligence based verification for 6G digital twin channel

REM-U-Net: Deep Learning Based Agile REM Prediction With Energy-Efficient Cell-Free Use Case

Rigorous Indoor Wireless Communication System Simulations With Deep Learning-Based Radio Propagation Models

A Deep-Learning Approach to a Volumetric Radio Environment Map Construction for UAV-Assisted Networks

Super-Resolution of Wireless Channel Characteristics: A Multitask Learning Model

Cell-Level RSRP Estimation With the Image-to-Image Wireless Propagation Model Based on Measured Data

Accurate Spectrum Map Construction for Spectrum Management Through Intelligent Frequency-Spatial Reasoning

A Graph Neural Network Based Radio Map Construction Method for Urban Environment

A Deep Learning-Based Indoor Radio Estimation Method Driven by 2.4 GHz Ray-Tracing Data

A FL-Based Radio Map Reconstruction Approach for UAV-Aided Wireless Networks

Multi-Stage RF Emitter Search and Geolocation With UAV: A Cognitive Learning-Based Method

DeepREM: Deep-Learning-Based Radio Environment Map Estimation From Sparse Measurements

RME-GAN: A Learning Framework for Radio Map Estimation Based on Conditional Generative Adversarial Network

A Deep Learning-Based Indoor Radio Estimation Method Driven by 2.4 GHz Ray-Tracing Data

Temporal prediction for spectrum environment maps with moving radiation sources

Machine Learning-Based Urban Canyon Path Loss Prediction Using 28 GHz Manhattan Measurements

Pseudo Ray-Tracing: Deep Leaning Assisted Outdoor mm-Wave Path Loss Prediction

Fast Radio Propagation Prediction with Deep Learning

An Overview of Propagation Models BasElectriacaled on Deep Learning Techniques

An Empirical Study on Using CNNs for Fast Radio Signal Prediction

Machine Learning-Based Radio Coverage Prediction in Urban Environments

Radiomap Inpainting for Restricted Areas Based on Propagation Priority and Depth Map

Conference

RadioDiff-Turbo: Lightweight Generative Large Electromagnetic Model for Wireless Digital Twin Construction

Radio Map Reconstruction Based on Nas Enhanced Deep Regularization Completion for Uav Communications

DULRTC-RME: A Deep Unrolled Low-rank Tensor Completion Network for Radio Map Estimation

FedRME: Importance-Aware Cooperative Radio Map Estimation Empowered by Vertical Federated Learning

A Diffusion-Based Propagation Model for Path Loss Prediction in Indoor Environments

RadioDiff-Turbo: Lightweight Generative Large Electromagnetic Model for Wireless Digital Twin Construction （UNIC）

UNet-Based Deep Learning Pathloss Estimator with Boundary Condition Input

Learning Blockage and Reflection Geometry for MIMO Beam Map Construction

Environment-Aware AoD and AoA Prediction for Wireless Networks Utilizing Machine Learning

Channel-Aware Deep Learning for Superimposed Pilot Power Allocation and Receiver Design

Ultra-Grained Channel Fingerprint Construction via Conditional Generative Diffusion Models

Radio Map Estimation via Latent-Domain Plug-and-Play Denoisers

IPP-Net: A Generalizable Deep Neural Network Model for Indoor Pathloss Radio Map Prediction

Spatial Transformers for Radio Map Estimation

Generative CKM construction using partially observed data with diffusion model

Deep Learning-Based CKM Construction with Image Super-Resolution

Data-and-Semantic Dual-Driven Spectrum Map Construction for 6G Spectrum Management

Channel Knowledge Map Construction with Laplacian Pyramid Reconstruction Network

Machine Learning-based Predictive Channel Modeling for 6G Wireless Communications Using Image Semantic Segmentation

Radio Map Estimation with Deep Dual Path Autoencoders and Skip Connection Learning

FedRME: Federated Learning for Enhanced Distributed Radiomap Estimation

Channel Knowledge Maps Construction Based on Point Cloud Environment Information

A Transformer-Based Network for Unifying Radio Map Estimation and Optimized Site Selection

Fine Tuning an AI-Based Indoor Radio Propagation Model with Crowd-Sourced Data

Distributed Radio Map Reconstruction Based on Semi-Asynchronous Federated Learning Generative Adversarial Networks

RobUNet: A Radio Map Construction Method with A Strong Generalization Capability

A 2D Deep Residual Learning Approach for 3D Indoor Radio Map Estimation

Towards the Metaverse: Distributed Radio Map Reconstruction based on Federated Learning Generative Adversarial Networks

Optimal Base Station Sleep Control via Multi-Agent Reinforcement Learning with Data-Driven Radio Environment Map Calibration

A Bayesian Learning Approach to Wireless Outdoor Heatmap Construction Using Deep Gaussian Process

A New Approach to Predict Radio Map via Learning-Based Spatial Loss Field

RecuGAN: A Novel Generative AI Approach for Synthesizing RF Coverage Maps

Radio Map Reconstruction Based on Transformer from Sparse Measurement

Deep Learning-Based Radio Estimation Using a Semi-Automatically Created Indoor Building Information

Evaluation of Transformer Empowered Channel Prediction for 5G and Beyond Communication

Radio Map Estimation (RME) with Deep Progressive Network

Fast Indoor Radio Propagation Prediction using Deep Learning

Deep Machine Learning-Based AoD Map and AoA Map Construction for Wireless Networks

RM-Gen: Conditional Diffusion Model-Based Radio Map Generation for Wireless Networks

Data-Driven Radio Environment Map Estimation Using Graph Neural Networks

Fast and Accurate Cooperative Radio Map Estimation Enabled by GAN

A Transformer-Based Network for Unifying Radio Map Estimation and Optimized Site Selection

Radio DIP - Completing Radio Maps using Deep Image Prior

Deep Learning-Based Path Loss Prediction for Outdoor Wireless Communication Systems

Agile Radio Map Prediction Using Deep Learning

Transformer-Based Neural Surrogate for Link-Level Path Loss Prediction from Variable-Sized Maps

IRGAN: cGAN-based Indoor Radio Map Prediction

IndoorRSSINet - Deep learning based 2D RSSI map prediction for indoor environments with application to wireless localization

UnetRay: A Prediction Method of Indoor Radio Signal Strength Distribution

Locswinunet: A Neural Network for Urban Wireless Localization Using TOA and RSS Radio Maps

Three-Dimensional Radio Spectrum Map Prediction Based on Fully Connected Neural Network

Federated Learning-Based Radio Environment Map Construction for Wireless Networks

Propagation Graph Representation Learning and Its Implementation in Direct Path Representation

UAV-aided Joint Radio Map and 3D Environment Reconstruction using Deep Learning Approaches

A Multi-Task Learning Model for Super Resolution of Wireless Channel Characteristics

Deep Transfer Learning Based Radio Map Estimation for Indoor Wireless Communications

LocUNet: Fast Urban Positioning Using Radio Maps and Deep Learning

Deep Transfer Learning Based Radio Map Estimation for Indoor Wireless Communications

Learning Graph Convolutional Neural Networks to Predict Radio Environment Maps

RadioResUNet: Wireless Measurement by Deep Learning for Indoor Environments

Extending Machine Learning Based RF Coverage Predictions to 3D

Exemplar-Based Radio Map Reconstruction of Missing Areas Using Propagation Priority

Spatial Prediction of Channel Signal Strength Map Using Deep Fully Convolutional Neural Network

Transformer based Radio Map Prediction Model for Dense Urban Environments

Radio Map Estimation Using a Generative Adversarial Network and Related Business Aspects

Prediction of Indoor Wireless Coverage from 3D Floor Plans Using Deep Convolutional Neural Networks

ArXiv

RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Construction

GenMetaLoc: Learning to Learn Environment-Aware Fingerprint Generation for Sample Efficient Wireless Localization

Fusion of Pervasive RF Data with Spatial Images via Vision Transformers for Enhanced Mapping in Smart Cities

BS-1-to-N: Diffusion-Based Environment-Aware Cross-BS Channel Knowledge Map Generation for Cell-Free Networks

Channel Fingerprint Construction for Massive MIMO: A Deep Conditional Generative Approach

PINN and GNN-based RF Map Construction for Wireless Communication Systems

RMTransformer: Accurate Radio Map Construction and Coverage Prediction

LLM4MG: Adapting Large Language Model for Multipath Generation via Synesthesia of Machines

Machine Learning based Radio Environment Map Estimation for Indoor Visible Light Communication

Bayesian Radio Map Estimation: Fundamentals and Implementation via Diffusion Models

RadioDUN: A Physics-Inspired Deep Unfolding Network for Radio Map Estimation

RadioFormer: A Multiple-Granularity Radio Map Estimation Transformer with 1\textpertenthousand Spatial Sampling

RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimation

Temporal Spectrum Cartography in Low-Altitude Economy Networks: A Generative AI Framework with Multi-Agent Learning

ExposNet: A Deep Learning Framework for EMF Exposure Prediction in Complex Urban Environments

GenMetaLoc: Learning to Learn Environment-Aware Fingerprint Generation for Sample Efficient Wireless Localization

FERMI: Flexible Radio Mapping with a Hybrid Propagation Model and Scalable Autonomous Data Collection

Solving Maxwell's equations with Non-Trainable Graph Neural Network Message Passing

Radio Map Estimation -- An Open Dataset with Directive Transmitter Antennas and Initial Experiments

A Deep Unfolding-Based Scalarization Approach for Power Control in D2D Networks

Simulating, Fast and Slow: Learning Policies for Black-Box Optimization

White Paper on Radio Channel Modeling and Prediction to Support Future Environment-aware Wireless Communication Systems

Deep Learning Based Active Spatial Channel Gain Prediction Using a Swarm of Unmanned Aerial Vehicles

RadioNet: Transformer based Radio Map Prediction Model For Dense Urban Environments