… CSI encoding has been used in a closed-loop MIMO system. Different from [14], which has
… consider a simple single-cell downlink massive MIMO system with Nt ≫ 1 transmit antennas …

… proposes a deep-learning-enabled mmWave massive MIMO … as a mapping relation in
the deep neural network (DNN). … process of the mmWave massive MIMO. Additionally, we …

… We consider the downlink of a massive MIMO system, in which the transmitter is equipped
with Nt antennas and the receiver is equipped with Nr antennas. The channel from the …

… significant impact on the massive MIMO receivers’ performance … in data detection based on
the deep learning (DL) approach. DL … We garner the DL based massive MIMO detectors and …

… In this section, we propose a deep learning based scheme in massive MIMO system to
achieve super-resolution channel estimation. We consider the sparse case, in which the covari…

… learn the GM parameters from current estimated data. In this article, we present our initial
results in deep learning for beamspace mmWave massive MIMO … use deep learning technology …

… deep learning for solving the max-min and max-prod power allocation problems in the DL of
Massive MIMO … machine learning techniques [5] that demonstrate the ability of deep neural …

… Abstract—In this paper, we propose a data-driven deep learn… massive multiple-input
multiple-output (MIMO) systems. By exploiting the angular-domain compressibility of massive MIMO …

… having a generic MIMO dataset for deep learning applications, … In mmWave and massive
MIMO research, the main signal … and massive MIMO applications for machine learning relied on …

… In this paper, we have proposed a deep learning approach for downlink precoder design
in massive MIMO, making use of channel estimates and statistical parameters of channel …