4 papers · 1 filter
Model-based Deep Learning for Beam Prediction based on a Channel Chart
Taha Yassine, Baptiste Chatelier, Vincent Corlay +4
Channel charting builds a map of the radio environment in an unsupervised way. The obtained chart locations can be seen as low-dimensional compressed versions of channel state info…
Semi-Supervised End-to-End Learning for Integrated Sensing and Communications
José Miguel Mateos-Ramos, Baptiste Chatelier, Christian Häger +3
Integrated sensing and communications (ISAC) is envisioned as one of the key enablers of next-generation wireless systems, offering improved hardware, spectral, and energy efficien…
Model-based learning for location-to-channel mapping
Baptiste Chatelier, Luc Le Magoarou, Vincent Corlay +1
Modern communication systems rely on accurate channel estimation to achieve efficient and reliable transmission of information. As the communication channel response is highly rela…
Influence of Dataset Parameters on the Performance of Direct UE Positioning via Deep Learning
Baptiste Chatelier, Vincent Corlay, Cristina Ciochina +2
User equipment (UE) positioning accuracy is of paramount importance in current and future communications standard. However, traditional methods tend to perform poorly in non line o…