iRadioDiff: Physics-Informed Diffusion Model for Indoor Radio Map Construction and Localization

• URL: http://arxiv.org/abs/2511.20015v1
• Date: Tue, 25 Nov 2025 07:32:49 GMT
• Title: iRadioDiff: Physics-Informed Diffusion Model for Indoor Radio Map Construction and Localization
• Authors: Xiucheng Wang, Tingwei Yuan, Yang Cao, Nan Cheng, Ruijin Sun, Weihua Zhuang,
• Abstract summary: iRadioDiff is a sampling-free diffusion-based framework for indoor RM construction.<n>iRadioDiff achieves state-of-the-art performance in indoor RM construction and received signal strength based indoor localization.
• Score: 28.221749064585484
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Radio maps (RMs) serve as environment-aware electromagnetic (EM) representations that connect scenario geometry and material properties to the spatial distribution of signal strength, enabling localization without costly in-situ measurements. However, constructing high-fidelity indoor RMs remains challenging due to the prohibitive latency of EM solvers and the limitations of learning-based methods, which often rely on sparse measurements or assumptions of homogeneous material, which are misaligned with the heterogeneous and multipath-rich nature of indoor environments. To overcome these challenges, we propose iRadioDiff, a sampling-free diffusion-based framework for indoor RM construction. iRadioDiff is conditioned on access point (AP) positions, and physics-informed prompt encoded by material reflection and transmission coefficients. It further incorporates multipath-critical priors, including diffraction points, strong transmission boundaries, and line-of-sight (LoS) contours, to guide the generative process via conditional channels and boundary-weighted objectives. This design enables accurate modeling of nonstationary field discontinuities and efficient construction of physically consistent RMs. Experiments demonstrate that iRadioDiff achieves state-of-the-art performance in indoor RM construction and received signal strength based indoor localization, which offers effective generalization across layouts and material configurations. Code is available at https://github.com/UNIC-Lab/iRadioDiff.

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