Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) has been
regarded to be an emerging solution for the next generation of communications, in which …

In multi-user millimeter wave (mmWave) multiple-input-multiple-output (MIMO) systems,
hybrid precoding is a crucial task to lower the complexity and cost while achieving a …

This paper proposes a novel neural network architecture, that we call an auto-precoder. This
auto-precoder network jointly senses the millimeter wave (mmWave) channel and designs …

Channel estimation and hybrid precoding are considered for multi-user millimeter wave
massive multi-input multi-output system. A deep learning compressed sensing (DLCS) …

Hybrid precoding is a promising technique for mmWave massive MIMO systems, as it can
considerably reduce the number of required radio-frequency (RF) chains without obvious …

Due to high costs and power consumptions, fully digital baseband precoding schemes are
usually prohibitive in millimeter-wave massive MIMO systems. Therefore, hybrid precoding …

Channel estimation is one of the foremost challenges for realizing practical millimeter-wave
(mmWave) massive multiple-input multiple-output (MIMO) systems. To circumvent this …

Hybrid analog-digital precoding is challenging for broadband millimeter-wave (mmWave)
massive MIMO systems, since the analog precoder is frequency-flat but the mmWave …

Millimeter wave (mmWave) massive MIMO can achieve orders of magnitude increase in
spectral and energy efficiency, and it usually exploits the hybrid analog and digital …

For millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems,
hybrid processing architecture is usually used to reduce the complexity and cost, which …