14 citations · 29 across the 6 of their papers we have counts for
3 papers · 1 filter
Machine Learning-Based CSI Feedback With Variable Length in FDD Massive MIMO
Matteo Nerini, Valentina Rizzello, Michael Joham +2
To fully unlock the benefits of multiple-input multiple-output (MIMO) networks, downlink channel state information (CSI) is required at the base station (BS). In frequency division…
Learning the CSI Denoising and Feedback Without Supervision
Valentina Rizzello, Wolfgang Utschick
In this work, we develop a joint denoising and feedback strategy for channel state information in frequency division duplex systems. In such systems, the biggest challenge is the o…
Learning the CSI Recovery in FDD Systems
Wolfgang Utschick, Valentina Rizzello, Michael Joham +2
We propose an innovative machine learning-based technique to address the problem of channel acquisition at the base station in frequency division duplex systems. In this context, t…