2 citations · 5 across the 12 of their papers we have counts for
4 papers · 1 filter
CSI Compression using Channel Charting
Baptiste Chatelier, Vincent Corlay, Matthieu Crussière +1
Reaping the benefits of multi-antenna communication systems in frequency division duplex (FDD) requires channel state information (CSI) reporting from mobile users to the base stat…
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…
Efficient Deep Unfolding for SISO-OFDM Channel Estimation
Baptiste Chatelier, Luc Le Magoarou, Getachew Redieteab
In modern communication systems, channel state information is of paramount importance to achieve capacity. It is then crucial to accurately estimate the channel. It is possible to…
Deep learning for location based beamforming with NLOS channels
Luc Le Magoarou, Taha Yassine, Stéphane Paquelet +1
Massive MIMO systems are highly efficient but critically rely on accurate channel state information (CSI) at the base station in order to determine appropriate precoders. CSI acqui…