We propose a versatile feedback scheme for both single-and multi-user multiple-input
multiple-output (MIMO) frequency division duplex (FDD) systems. Particularly, we propose …

In this manuscript, we propose to utilize the generative neural network-based variational
autoencoder for channel estimation. The variational autoencoder models the underlying true …

In this work, we propose two methods that utilize data symbols in addition to pilot symbols for
improved channel estimation quality in a multi-user system, so-called semi-blind channel …

Recently, a versatile limited feedback scheme based on a Gaussian mixture model (GMM)
was proposed for frequency division duplex (FDD) systems. This scheme provides high …

This work introduces a novel class of channel estimators tailored for coarse quantization
systems. The proposed estimators are founded on conditionally Gaussian latent generative …

This work proposes a generative modeling-aided channel estimator based on mixtures of
factor analyzers (MFA). In an offline step, the parameters of the generative model are …

Abstract Orthogonal Frequency Division Multiplexing (OFDM) systems are prone to signal
corruption caused by strong and frequent impulses, which can be further exacerbated by …