2 papers
eess.SP2024
Neural 5G Indoor Localization with IMU Supervision
Aleksandr Ermolov, Shreya Kadambi, Maximilian Arnold +8
Radio signals are well suited for user localization because they are ubiquitous, can operate in the dark and maintain privacy. Many prior works learn mappings between channel state…
cs.LG2023
Transformer-Based Neural Surrogate for Link-Level Path Loss Prediction from Variable-Sized Maps
Thomas M. Hehn, Tribhuvanesh Orekondy, Ori Shental +7
Estimating path loss for a transmitter-receiver location is key to many use-cases including network planning and handover. Machine learning has become a popular tool to predict wir…