EnvCoLoc combines environment-conditioned diffusion meta-learning with 3D point cloud descriptors to reduce mean localization error by up to 20% in NLOS WiFi scenarios using only 10 support samples.
Constructing indoor region-based radio map without location labels
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2026 2verdicts
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An HMM-based coarse-to-fine framework constructs radio maps from unlabeled RSS sequences in unidirectional corridor environments, reporting 8.96 dB MAE and enabling 3.33 m KNN localization accuracy.
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Environment-Conditioned Diffusion Meta-Learning for Data-Efficient WiFi Localization
EnvCoLoc combines environment-conditioned diffusion meta-learning with 3D point cloud descriptors to reduce mean localization error by up to 20% in NLOS WiFi scenarios using only 10 support samples.
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Survey-Free Radio Map Construction via HMM-Based Coarse-to-Fine Inference
An HMM-based coarse-to-fine framework constructs radio maps from unlabeled RSS sequences in unidirectional corridor environments, reporting 8.96 dB MAE and enabling 3.33 m KNN localization accuracy.