Radiomap Inpainting for Restricted Areas based on Propagation Priority and Depth Map
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Abstract (arXiv)
Providing rich and useful information regarding spectrum activities and propagation channels, radiomaps characterize the detailed distribution of power spectral density (PSD) and are important tools for network planning in modern wireless systems. Generally, radiomaps are constructed from radio strength measurements by deployed sensors and user devices. However, not all areas are accessible for radio measurements due to physical constraints and security consideration, leading to non-uniformly spaced measurements and blanks on a radiomap. In this work, we explore distribution of radio spectrum strengths in view of surrounding environments, and propose two radiomap inpainting approaches for the reconstruction of radiomaps that cover missing areas. Specifically, we first define a propagation-based priority and integrate exemplar-based inpainting with radio propagation model for fine-resolution small-size missing area reconstruction on a radiomap. Then, we introduce a novel radio depth map and propose a two-step template-perturbation approach for large-size restricted region inpainting. Our experimental results demonstrate the power of the proposed propagation priority and radio depth map in capturing the PSD distribution, as well as the efficacy of the proposed methods for radiomap reconstruction.
Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 May 2023.
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Citing papers per year: 2024: 1; 2025: 7; 2026: 5.
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- 2024RadioGAT: A Joint Model-based and Data-driven Framework for Multi-band Radiomap Reconstruction via Graph Attention Networkscited by 16
- 2025RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Constructioncited by 11
- 2025AI-driven Wireless Positioning: Fundamentals, Standards, State-of-the-art, and Challengescited by 5
- 2025WiFi-Diffusion: Achieving Fine-Grained WiFi Radio Map Estimation With Ultra-Low Sampling Rate by Diffusion Modelscited by 4
- 2026Sparse Gain Radio Map Reconstruction With Geometry Priors and Uncertainty-Guided Measurement Selectioncited by 3
- 2025Physics-Inspired Distributed Radio Map Estimationcited by 2
- 2025EnvCDiff: Joint Refinement of Environmental Information and Channel Fingerprints via Conditional Generative Diffusion Modelcited by 1
- 2026Geometry-Aware Cross-Height Channel Knowledge Map Prediction for UAV-Assisted Communications With Uncertainty-Guided 3D Sensingcited by 1
- 2026QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networkscited by 1
- 2025RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimationcited by 0
- 2025RadioKMoE: Knowledge-Guided Radiomap Estimation with Kolmogorov-Arnold Networks and Mixture-of-Expertscited by 0
- 2026Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Frameworkcited by 0
- 2026QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks1 Jul 2026
- 2026Geometry-Aware Cross-Height Channel Knowledge Map Prediction for UAV-Assisted Communications With Uncertainty-Guided 3D Sensing1 Jul 2026
- 2026Diffusion Models for Radio Map Estimation: Theoretical Performance Analysis and Sampling Rate Guideline24 Jun 2026
- 2026Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework30 Apr 2026
- 2026Sparse Gain Radio Map Reconstruction With Geometry Priors and Uncertainty-Guided Measurement Selection7 Apr 2026
- 2025RadioKMoE: Knowledge-Guided Radiomap Estimation with Kolmogorov-Arnold Networks and Mixture-of-Experts21 Nov 2025
- 2025RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimation2 Sep 2025
- 2025EnvCDiff: Joint Refinement of Environmental Information and Channel Fingerprints via Conditional Generative Diffusion Model12 May 2025
- 2025RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Construction19 Apr 2025
- 2025WiFi-Diffusion: Achieving Fine-Grained WiFi Radio Map Estimation With Ultra-Low Sampling Rate by Diffusion Models15 Mar 2025
- 2025Physics-Inspired Distributed Radio Map Estimation1 Feb 2025
- 2025AI-driven Wireless Positioning: Fundamentals, Standards, State-of-the-art, and Challenges24 Jan 2025
- 2025WiFi-Diffusion: Achieving Fine-Grained WiFi Radio Map Estimation With Ultra-Low Sampling Rate by Diffusion Modelscited by 4
- 2025EnvCDiff: Joint Refinement of Environmental Information and Channel Fingerprints via Conditional Generative Diffusion Modelcited by 1
- 2025RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimationcited by 0
- 2026Diffusion Models for Radio Map Estimation: Theoretical Performance Analysis and Sampling Rate Guidelinecited by 0
- 2026Diffusion Models for Radio Map Estimation: Theoretical Performance Analysis and Sampling Rate Guideline24 Jun 2026
- 2025RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimation2 Sep 2025
- 2025EnvCDiff: Joint Refinement of Environmental Information and Channel Fingerprints via Conditional Generative Diffusion Model12 May 2025
- 2025WiFi-Diffusion: Achieving Fine-Grained WiFi Radio Map Estimation With Ultra-Low Sampling Rate by Diffusion Models15 Mar 2025
- 2024RadioGAT: A Joint Model-based and Data-driven Framework for Multi-band Radiomap Reconstruction via Graph Attention Networkscited by 16
- 2025RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Constructioncited by 11
- 2025AI-driven Wireless Positioning: Fundamentals, Standards, State-of-the-art, and Challengescited by 5
- 2026Sparse Gain Radio Map Reconstruction With Geometry Priors and Uncertainty-Guided Measurement Selectioncited by 3
- 2025Physics-Inspired Distributed Radio Map Estimationcited by 2
- 2026Geometry-Aware Cross-Height Channel Knowledge Map Prediction for UAV-Assisted Communications With Uncertainty-Guided 3D Sensingcited by 1
- 2026QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networkscited by 1
- 2026Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Frameworkcited by 0
- 2026QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks1 Jul 2026
- 2026Geometry-Aware Cross-Height Channel Knowledge Map Prediction for UAV-Assisted Communications With Uncertainty-Guided 3D Sensing1 Jul 2026
- 2026Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework30 Apr 2026
- 2026Sparse Gain Radio Map Reconstruction With Geometry Priors and Uncertainty-Guided Measurement Selection7 Apr 2026
- 2025RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Construction19 Apr 2025
- 2025Physics-Inspired Distributed Radio Map Estimation1 Feb 2025
- 2025AI-driven Wireless Positioning: Fundamentals, Standards, State-of-the-art, and Challenges24 Jan 2025
- 2024RadioGAT: A Joint Model-based and Data-driven Framework for Multi-band Radiomap Reconstruction via Graph Attention Networks25 Mar 2024