1 citations · 1 across the 14 of their papers we have counts for
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Supervised Device Charting with CSI Measurements from Commercial 5G NR User Equipments
Mischa Vasylyev, Frederik Zumegen, Reinhard Wiesmayr +1
Radio frequency fingerprint identification (RFFI) is a promising approach to distinguish physical wireless devices using hardware-induced signal imperfections. Conventional RFFI me…
On the Impact of Site-Specific Training for a Real-World 5G NR System
Reinhard Wiesmayr, Nuri Berke Baytekin, Chris Dick +1
Site-specific training can improve wireless receiver performance without increasing computational complexity. However, real-world results have so far focused on fully trainable neu…
Channel Charting for Position and Orientation
Daniel Richner, Reinhard Wiesmayr, Frederik Zumegen +1
Channel charting (CC) in real-world coordinates is a recently proposed self-supervised machine learning method that maps high-dimensional channel state information (CSI) to user eq…
Spatial and Temporal Generalization of CSI-based Neural Positioning
Till-Yannic Müller, Frederik Zumegen, Reinhard Wiesmayr +1
Channel state information (CSI)-based neural positioning learns a mapping from CSI measurements to user equipment (UE) positions using neural networks. However, most existing perfo…
SINR Estimation under Limited Feedback via Online Convex Optimization
Lorenzo Maggi, Boris Bonev, Reinhard Wiesmayr +2
We introduce a novel online convex optimization (OCO) framework to estimate the user's signal-to-interference-plus-noise ratio (SINR) from ACK/NACK feedback, channel quality indica…
Site-Specific Finetuning of Neural Receivers with Real-World 5G NR Measurements
Nuri Berke Baytekin, Reinhard Wiesmayr, Sebastian Cammerer +2
Finetuning wireless receivers to a specific deployment scenario can yield significant error-rate performance improvements without increasing processing complexity. However, site-sp…