arXiv AI

GLocFM: A Geometry-Aware Foundation Model for 3D Indoor Wireless Localization

arXiv:2608. 09285v1 Announce Type: cross Abstract: Learning-based wireless localizers often fail to utilize geometric information about the propagation environment, limiting their ability to exploit non-line-of-sight (NLoS) propagation and generalize across scenes.

arXiv Machine Learning
Jun 11

OmniLoc: A Geometry-Aware Foundation Model for Anchor-Free UE Localization Across Diverse Indoor Environments

arXiv:2606. 11490v1 Announce Type: new Abstract: Indoor localization from wireless measurements remains challenging in large-scale deployments due to substantial variation in building geometry, the set of detectable access points (APs), and the heterogeneity of received signals.

By Lei Chu, Yuning Zhang, Omer Gokalp Serbetci, Anushka Katiyar, Bassel Abou Ali Modad, Andreas F. Molisch
arXiv Machine Learning
Jun 30

RadarTwin: Scene-Specific mmWave Radar Simulation and Learning for Mobile Indoor Perception

arXiv:2606. 28396v1 Announce Type: cross Abstract: Millimeter-wave (mmWave) radar perception is limited by data scarcity: models trained on existing radar datasets fail to generalize to new objects, environments, and sensing trajectories.

By Emily Bejerano, Federico Tondolo, Devang Gupta, Aaron Mano Cherian, Taeyoo Kim, Ayaan Qayyum, Xiaofan Yu, Xiaofan Jiang