4 papers · 1 filter
POPT: Physics-Informed Deep Learning for Phase-Only Positioning in Distributed MIMO
Fatih Ayten, Ossi Kaltiokallio, Jukka Talvitie +6
This article develops a physics-informed deep learning framework for single-snapshot 3D phase-only positioning in narrowband phase-coherent distributed multiple-input multiple-outp…
Phase-Only Positioning in Distributed MIMO Under Phase Impairments: AP Selection Using Deep Learning
Fatih Ayten, Musa Furkan Keskin, Akshay Jain +5
Carrier phase positioning (CPP) can enable cm-level accuracy in next-generation wireless systems, while recent literature shows that accuracy remains high using phase-only measurem…
Failure Tolerant Phase-Only Indoor Positioning via Deep Learning
Fatih Ayten, Mehmet C. Ilter, Akshay Jain +5
High-precision localization turns into a crucial added value and asset for next-generation wireless systems. Carrier phase positioning (CPP) enables sub-meter to centimeter-level a…
Phase-Only Positioning: Overcoming Integer Ambiguity Challenge through Deep Learning
Fatih Ayten, Mehmet C. Ilter, Ossi Kaltiokallio +5
This paper investigates uplink carrier phase positioning (CPP) in cell-free (CF) or distributed antenna system context, assuming a challenging case where only phase measurements ar…