To estimate time-varying MIMO channel at base station, traditional downlink (DL) channel
restoration schemes usually require the reconstruction for the covariance of downlink …

In frequency division duplex massive MIMO systems, one critical challenge is that the
mobiles need to feed back a large downlink channel matrix to the base station, creating …

The low-rank property of the channel covariances can be adopted to reduce the overhead of
the channel training in massive MIMO systems. In this paper, with the help of the virtual …

Massive MIMO is considered as one key enabling technology in 5G communications.
Although the high-quality channel state information (CSI) estimation is essential to improve …

This paper addresses the problem of massive multiple-input multiple-output (MIMO) channel
estimation in the presence of impulsive noise. In the literature, a sparse Bayesian learning …

We consider efficient channel estimation for massive multiple-input multiple-output (MIMO)
systems using one-bit analog-to-digital converters (ADCs) with antenna-varying thresholds …

This letter provides a novel hierarchical-block channel estimation scheme for massive
multiple-input multiple-output (MIMO) systems based on Bayesian learning frameworks …

In this letter, we formulate an off-grid channel model to characterize spatial sample
mismatching in the discrete Fourier transform (DFT) based massive multiple-input-multiple …

Massive MIMO channel has a sparse representation in the angular domain, but it is difficult
to utilize such sparsity for uplink channel estimation due to the coupling effect caused by …

Due to its enhanced capacity and energy efficiency, massive MIMO has become a critical
technology for the 5 G and beyond mobile networks. However, fully achieving its benefits …