mlsanityData to 14 Oct 2026

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

arXiv 2212.12817 ↗First posted 24 Dec 2022eess.SPcited by 50

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Abstract (arXiv)

Outdoor radio map estimation is an important tool for network planning and resource management in modern Internet of Things (IoT) and cellular systems. Radio map describes spatial signal strength distribution and provides network coverage information. A practical goal is to estimate fine-resolution radio maps from sparse radio strength measurements. However, non-uniformly positioned measurements and access obstacles can make it difficult for accurate radio map estimation (RME) and spectrum planning in many outdoor environments. In this work, we develop a two-phase learning framework for radio map estimation by integrating radio propagation model and designing a conditional generative adversarial network (cGAN). We first explore global information to extract the radio propagation patterns. We then focus on the local features to estimate the effect of shadowing on radio maps in order to train and optimize the cGAN. Our experimental results demonstrate the efficacy of the proposed framework for radio map estimation based on generative models from sparse observations in outdoor scenarios.

Key facts. Cited by 50 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Dec 2022.

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Citing papers per year: 2023: 1; 2024: 7; 2025: 24; 2026: 18.

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  1. 2024RadioDiff: An Effective Generative Diffusion Model for Sampling-Free Dynamic Radio Map Constructioncited by 56
  2. 2025RadioDiff-k2: Helmholtz Equation Informed Generative Diffusion Model for Multi-Path Aware Radio Map Constructioncited by 19
  3. 2023Generative AI for Physical Layer Communications: A Surveycited by 17
  4. 2024RadioGAT: A Joint Model-based and Data-driven Framework for Multi-band Radiomap Reconstruction via Graph Attention Networkscited by 17
  5. 2025RadioDiff-3D: A 3D×3D Radio Map Dataset and Generative Diffusion Based Benchmark for 6G Environment-Aware Communicationcited by 16
  6. 2024Generative AI on SpectrumNet: An Open Benchmark of Multiband 3D Radio Mapscited by 14
  7. 2025Generative Diffusion Models for Wireless Networks: Fundamental, Architecture, and State-of-the-Artcited by 14
  8. 2025RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Constructioncited by 11
  9. 2024ACT-GAN: Radio map construction based on generative adversarial networks with ACT blockscited by 6
  10. 2025CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priorscited by 6
  11. 2025AI-driven Wireless Positioning: Fundamentals, Standards, State-of-the-art, and Challengescited by 5
  12. 2025RadioMamba: Breaking the Accuracy-Efficiency Trade-off in Radio Map Construction via a Hybrid Mamba-UNetcited by 5
38 more
  1. 2024Generative CKM Construction using Partially Observed Data with Diffusion Modelcited by 4
  2. 2025A Disentangled Representation Learning Framework for Low-altitude Network Coverage Predictioncited by 4
  3. 2026RadioDiff-Flux: Efficient Radio Map Construction via Generative Denoise Diffusion Model Trajectory Midpoint Reusecited by 4
  4. 2026U6G XL-MIMO Radiomap Prediction: Multi-Config Dataset and Beam Map Approachcited by 4
  5. 2026BeamCKMDiff: Beam-Aware Channel Knowledge Map Construction via Diffusion Transformercited by 3
  6. 2024Deep Learning-Based CKM Construction with Image Super-Resolutioncited by 2
  7. 2025Physics-Inspired Distributed Radio Map Estimationcited by 2
  8. 2025RadioDUN: A Physics-Inspired Deep Unfolding Network for Radio Map Estimationcited by 2
  9. 2025Agentic Satellite-Augmented Low-Altitude Economy and Terrestrial Networks: A Survey on Generative Approachescited by 2
  10. 2025iRadioDiff: Physics-Informed Diffusion Model for Indoor Radio Map Construction and Localizationcited by 2
  11. 2026Channel Knowledge Map Construction via Guided Flow Matchingcited by 2
  12. 2026RadioDiff-FS: Physics-Informed Manifold Alignment in Few-Shot Diffusion Models for High-Fidelity Radio Map Constructioncited by 2
  13. 2024CF-CGN: Channel Fingerprints Extrapolation for Multi-band Massive MIMO Transmission based on Cycle-Consistent Generative Networkscited by 1
  14. 2025Data-and-Semantic Dual-Driven Spectrum Map Construction for 6G Spectrum Managementcited by 1
  15. 2025Generative AI Meets Wireless Sensing: Towards Wireless Foundation Modelcited by 1
  16. 2025RadioFlow: Efficient Radio Map Construction Framework with Flow Matchingcited by 1
  17. 20253D Dynamic Radio Map Prediction Using Vision Transformers for Low-Altitude Wireless Networkscited by 1
  18. 2025Channel Knowledge Map Construction via Physics-Inspired Diffusion Model Without Prior Observationscited by 1
  19. 2026QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networkscited by 1
  20. 2025MARS: Radio Map Super-resolution and Reconstruction Method under Sparse Channel Measurementscited by 0
  21. 2025UrbanMIMOMap: A Ray-Traced MIMO CSI Dataset with Precoding-Aware Maps and Benchmarkscited by 0
  22. 2025Intelligent Optimization of Wireless Access Point Deployment for Communication-Based Train Control Systems Using Deep Reinforcement Learningcited by 0
  23. 2025Physics-Informed Neural Networks for MIMO Beam Map and Environment Reconstructioncited by 0
  24. 2025RadioKMoE: Knowledge-Guided Radiomap Estimation with Kolmogorov-Arnold Networks and Mixture-of-Expertscited by 0
  25. 2025Self-Localizing MIMO Beam Mapping with Continuously Evolving Channel Memorycited by 0
  26. 2025RadioMapMotion: A Dataset and Baseline for Proactive Spatio-Temporal Radio Environment Predictioncited by 0
  27. 2026RadioGen3D: 3D Radio Map Generation via Adversarial Learning on Large-Scale Synthetic Datacited by 0
  28. 2026RMPrior: Bridging Propagation Priors and Diffusion Refinement for Efficient Radio Map Constructioncited by 0
  29. 2026Diffusion Models for Radio Map Estimation: Theoretical Performance Analysis and Sampling Rate Guidelinecited by 0
  30. 2026Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Modelscited by 0
  31. 2026Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completioncited by 0
  32. 2026RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localizationcited by 0
  33. 2026RadioTrace: Transmitter-Aware Diffusion for Radio Map Estimation without Deployment-Time Fine-Tuningcited by 0
  34. 2026Physics-informed VAE-EVT for Tail Aware Radio Map Predictioncited by 0
  35. 2026RadioVIL: Anomaly-Aware Diffusion Models for Radio Map Inpainting and Zero-Shot Vehicle Localizationcited by 0
  36. 2026BeamRMX: Radiation-Pattern-Driven Learning for Generalizable Beam Radio Map Prediction and Beam Managementcited by 0
  37. 2026Rethinking Radiomap Blind Prediction with Limited Environment and Configuration Representationscited by 0
  38. 2026Radiomap Blind Prediction under Incomplete Observation: Error Characterization and Correctable Propagation-Prior Learningcited by 0