This paper investigates downlink (DL) channel estimation of frequency division duplex
(FDD) massive multiple-input-multiple-output (MIMO) with a finite number of base station …

Accurate channel state information (CSI) is critical to harvest the potential gain brought by
massive multiple-input multiple-output (MIMO). However, the acquisition of downlink CSI is …

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 …

In frequency-division duplexing systems, the downlink channel state information (CSI)
acquisition scheme leads to high training and feedback overhead. In this work, we propose …

Cell-free massive multiple-input multiple-output (CF-mMIMO) provides a consistent service
experience for the users that use mobile terminals. In frequency division duplexing (FDD) …

Massive multiple-input multiple-output (MIMO) is envisioned to meet the growing spectral
efficiency (SE) requirement in next generation cellular systems. However, it has been …

Hybrid beamforming (BF) is a promising solution for massive MIMO with limited RF chains.
To reduce the amount of pilot overhead for channel estimation, compressed sensing …

Massive MIMO systems are being incorporated in 5G wireless networks owing to its high
spectral efficiency. In order to achieve this efficiency, we require accurate Channel State …

In cellular systems, deploying a large number of antennas at the base station (BS), also
called massive multiple-input multiple-output (MIMO), can offer a huge improvement in …

In this letter, a novel minimum mean square error (MSE) based channel estimation
framework is proposed to reduce the downlink channel training overhead in frequency …