We propose a Bayesian deep learning framework for model driven online sparse channel
estimation task in Multi-user MIMO systems. Tools from Bayesian neural network and …

Channel estimation is crucial to beamforming techniques in directional millimetre wave
(mmWave) communications, which is generally designed based on channel state …

We consider the problem of uplink channel estimation for millimeter wave (mmWave)
systems, where the base station (BS) and mobile stations (MSs) are equipped with large …

Channel estimation is a critical task in multiple-input multiple-output (MIMO) digital
communications that substantially affects end-to-end system performance. In this work, we …

Sparse, group-sparse and online channel estimation is conceived for millimeter wave
(mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing …

To perform multi-user multiple-input and multipleoutput transmission in millimeter-wave
(mmWave) cellular systems, the high-dimensional channels need to be estimated for …

Millimeter-wave (mmWave) communications will play an important role in 5G and 6G
communication systems as a means to support extremely high data rates. One main …

This letter tackles the problem of channel estimation in mmWave multiple-input single-output
systems, where users are equipped with single-antenna receivers. By leveraging broadcast …

This paper is concerned with the channel estimation problem in multi-user millimeter wave
wireless systems with large antenna arrays. We develop a novel simultaneous-estimation …

This paper addresses the problem of joint downlink channel estimation and user grouping in
massive multiple-input multiple-output (MIMO) systems, where the motivation comes from …