2 papers
eess.SP2025
Demonstrating Interoperable Channel State Feedback Compression with Machine Learning
Dani Korpi, Rachel Wang, Jerry Wang +20
Neural network-based compression and decompression of channel state feedback has been one of the most widely studied applications of machine learning (ML) in wireless networks. Var…
eess.SP2025
SwinLSTM Autoencoder for Temporal-Spatial-Frequency Domain CSI Compression in Massive MIMO Systems
Aakash Saini, Yunchou Xing, Jee Hyun Kim +2
This study presents a parameter-light, low-complexity artificial intelligence/machine learning (AI/ML) model that enhances channel state information (CSI) feedback in wireless syst…