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 …

Recently, compressive sensing based massive multiple input multiple output (MIMO)
channel estimation (CE) has attracted intensive research interest. By exploiting the …

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 …

In order to realize the advantages of the massive MIMO systems, the channel state
information must be obtained at the base station (BS). However, it is a challenging task in …

We study downlink channel estimation in a multi-cell Massive multiple-input multiple-output
(MIMO) system operating in time-division duplex. The users must know their effective …

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 …

Pilot contamination posts a fundamental limit on the performance of massive multiple-input-
multiple-output (MIMO) antenna systems due to failure in accurate channel estimation. To …

Sparse angular reciprocity refers to the fact that downlink and uplink channels share
common sparsity in angular domain. This sophisticated sparsity can be exploited to improve …

The quasi-static assumption of channels becomes invalid in a number of emerging
applications of massive multiple-input multiple-output (MIMO) systems with high base station …

Obtaining channel covariance knowledge is of great importance in various Multiple-Input
Multiple-Output MIMO communication applications, including channel estimation and user …