4 citations · 4 across the 3 of their papers we have counts for
3 papers
Radio Foundation Models: Pre-training Transformers for 5G-based Indoor Localization
Jonathan Ott, Jonas Pirkl, Maximilian Stahlke +2
Artificial Intelligence (AI)-based radio fingerprinting (FP) outperforms classic localization methods in propagation environments with strong multipath effects. However, the model…
Indoor Localization with Robust Global Channel Charting: A Time-Distance-Based Approach
Maximilian Stahlke, George Yammine, Tobias Feigl +2
Fingerprinting-based positioning significantly improves the indoor localization performance in non-line-of-sight-dominated areas. However, its deployment and maintenance is cost-in…
Position Tracking using Likelihood Modeling of Channel Features with Gaussian Processes
Sebastian Kram, Christopher Kraus, Tobias Feigl +3
Recent localization frameworks exploit spatial information of complex channel measurements (CMs) to estimate accurate positions even in multipath propagation scenarios. State-of-th…