This paper addresses downlink channel estimation for frequency division duplex multi-user
massive multiple-input multiple-output systems. Suppose that a base station communicates …

We design a centralized and a decentralized variational Bayesian learning (C-and D-VBL)
algorithms for the base station (BS) of a frequency division duplex massive multiple input …

We consider the problem of downlink training and channel estimation in frequency division
duplex (FDD) massive MIMO systems, where the base station (BS) equipped with a large …

Massive multiple-input multiple-output (MIMO) is one of the most promising techniques for
next generation wireless communications due to its superior capability to provide high …

Pilot contamination (PC) is a major problem in massive multiple-input multiple-output
(MIMO) systems. This paper proposes a novel channel estimation scheme for such a system …

In frequency-division-duplex (FDD) massive MIMO systems, channel state information (CSI)
feedback waiting phase does not get fully exploited since base station needs to wait for the …

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 …

Massive multiple-input multiple-output (MIMO) is believed to deliver unrepresented spectral
efficiency gains for 5G and beyond. However, a practical challenge arises during its …

Numerical evidence suggests that compressive sensing (CS) approaches for wideband
massive MIMO channel estimation can achieve very good performance with limited training …

In this paper we study the channel estimation problem for a CP-OFDM based hybrid analog-
digital massive MIMO system. In contrast to a conventional MIMO system, two additional …