Deep CNN-based channel estimation for mmWave massive MIMO systems
For millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems,
hybrid processing architecture is usually used to reduce the complexity and cost, which …
hybrid processing architecture is usually used to reduce the complexity and cost, which …
Channel estimation for mmWave massive MIMO with convolutional blind denoising network
Channel estimation is one of the foremost challenges for realizing practical millimeter-wave
(mmWave) massive multiple-input multiple-output (MIMO) systems. To circumvent this …
(mmWave) massive multiple-input multiple-output (MIMO) systems. To circumvent this …
Two-stage channel estimation for mmWave massive MIMO systems based on ResNet-UNet
J Zhao, Y Wu, Q Zhang, J Liao - IEEE Systems Journal, 2023 - ieeexplore.ieee.org
For millimeter wave massive multiple-input multiple-output systems, the transceiver usually
adopts a hybrid precoding structure to reduce complexity and cost, which poses great …
adopts a hybrid precoding structure to reduce complexity and cost, which poses great …
Sparsity-aware channel estimation for mmWave massive MIMO: A deep CNN-based approach
S Liu, X Huang - China Communications, 2021 - ieeexplore.ieee.org
The deep convolutional neural network (CNN) is exploited in this work to conduct the
challenging channel estimation for mmWave massive multiple input multiple output (MIMO) …
challenging channel estimation for mmWave massive multiple input multiple output (MIMO) …
Deep learning-based channel estimation for beamspace mmWave massive MIMO systems
Channel estimation is very challenging when the receiver is equipped with a limited number
of radio-frequency (RF) chains in beamspace millimeter-wave massive multiple-input and …
of radio-frequency (RF) chains in beamspace millimeter-wave massive multiple-input and …
Deep learning for beamspace channel estimation in millimeter-wave massive MIMO systems
X Wei, C Hu, L Dai - IEEE Transactions on Communications, 2020 - ieeexplore.ieee.org
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 …
to considerably reduce the number of radio frequency (RF) chains, but channel estimation is …
Channel estimation for cell-free mmWave massive MIMO through deep learning
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 …
with millimeter-wave (mmWave) bands is indeed one of most promising technological …
An AMP-based network with deep residual learning for mmWave beamspace channel estimation
Y Wei, MM Zhao, M Zhao, M Lei… - IEEE Wireless …, 2019 - ieeexplore.ieee.org
Beamspace channel estimation in millimeter-wave (mmWave) massive MIMO system is a
very challenging task, especially when the number of radio-frequency chains is limited. To …
very challenging task, especially when the number of radio-frequency chains is limited. To …
Deep learning-based frequency-selective channel estimation for hybrid mmWave MIMO systems
Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems typically
employ hybrid mixed signal processing to avoid expensive hardware and high training …
employ hybrid mixed signal processing to avoid expensive hardware and high training …
Deep learning-based beamspace channel estimation in mmWave massive MIMO systems
Y Zhang, Y Mu, Y Liu, T Zhang… - IEEE Wireless …, 2020 - ieeexplore.ieee.org
In this letter, fully convolutional denoising approximate message passing (FCDAMP)
algorithm is proposed by combining fully convolutional denoising networks with learned …
algorithm is proposed by combining fully convolutional denoising networks with learned …