channel-estimation

Proposes a message-passing-based two-timescale Bayesian deep learning framework for joint channel and memory hardware impairment tracking in massive MIMO systems.

PilotWiMAE introduces a self-supervised framework that directly ingests noisy pilot observations for wireless channel representation learning, removing the unrealistic full-CSI assumption and enabling robust cross-frequency beam selection and channel estimation that beats supervised baselines.