arXiv Machine Learning

WiFi-Based People Counting Using Beam-Steerable Antennas: A Test-bed Study

arXiv:2606. 23710v1 Announce Type: cross Abstract: Ubiquitous perception through RF signals is a pivotal opportunity for future technology: it enables personalized services such as smart living, remote healthcare, automated logistics or interaction through free-space gestures.

arXiv Machine Learning
Jul 7

Seeing Through WiFi: Lightweight Human Pose Estimation with Dynamic Kernel Attention

arXiv:2607. 03196v1 Announce Type: cross Abstract: WiFi-based human pose estimation (HPE) enables the detection and interpretation of human body positions and movements without the need for wearable devices while preserving individual privacy concerns.

By Toan D. Gian, Van-Dinh Nguyen, Vo Phi Son, Nhan Thanh Nguyen, Dinh Thai Hoang, Diep N. Nguyen, Nguyen Cong Luong, Symeon Chatzinotas
arXiv AI
Jul 14

Physics-Informed Structure Anchoring With Capture-Aware Prototype Calibration for Cross-Environment RF Fingerprinting

arXiv:2607. 09760v1 Announce Type: cross Abstract: Radio frequency fingerprint identification (RFFI) uses transmitter-specific hardware imperfections as a physicallayer identity cue for Internet of Things (IoT) devices, but deep RFFI models often degrade when the acquisition environment changes.

By Fengchong Yao, Jianbing Li, Qing Liu, Qikun Liu, Kefeng Song, Haitao Li, Song Wang
arXiv Machine Learning
Aug 10

RIS-Aided mmWave Localization Under Cross-Link Interference via Beam-Domain ML Fingerprinting

arXiv:2608. 07444v1 Announce Type: cross Abstract: Accurate user equipment (UE) localization is critical for beam management in reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) based sixth-generation (6G) networks, especially if the direct base-station-UE links are unavailable.

By Md Tarek Hassan, Dmitry Zelenchuk, Muhammad Ali Babar Abbasi
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