The recent concept of massive multiple-input multiple-output (MIMO) can significantly
improve the capacity of the communication network, and it has been regarded as a …

In this paper, we propose a data-driven deep learning (DL) approach to jointly design the
pilot signals and channel estimator for wideband massive multiple-input multiple-output …

Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) with hybrid
precoding is a promising technique for the future 5G wireless communications. Due to a …

Channel estimation is challenging for millimeter-wave massive MIMO with hybrid precoding,
since the number of radio frequency chains is much smaller than that of antennas …

One of the fundamental challenges to realize massive Multiple-Input Multiple-Output (MIMO)
communications is the accurate acquisition of channel state information for a plurality of …

Channel estimation is one of the key issues in practical massive multiple-input multiple-
output (MIMO) systems. Compared with conventional estimation algorithms, deep learning …

A critical bottleneck of massive multiple-input multiple-output (MIMO) system is the huge
training overhead caused by downlink transmission, like channel estimation, downlink …

The combination of cell-free massive multiple-input multiple-output (MIMO) systems along
with millimeter-wave (mmWave) bands is indeed one of most promising technological …

Millimeter-wave massive multiple-input multiple-output (MIMO) can use a lens antenna array
to considerably reduce the number of radio frequency (RF) chains, but channel estimation is …

In this letter, we propose a deep learning (DL)-based channel estimation scheme for the
massive multiple-input multiple-output (MIMO) system. Unlike existing studies, we develop …