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 for fast channel estimation in millimeter-wave MIMO systems
S Lyu, X Li, T Fan, J Liu, M Shi - Journal of systems engineering …, 2022 - ieeexplore.ieee.org
Channel estimation has been considered as a key issue in the millimeter-wave (mmWave)
massive multi-input multi-output (MIMO) communication systems, which becomes more …
massive multi-input multi-output (MIMO) communication systems, which becomes more …
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 …
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 …
Deep learning-based channel estimation for wideband hybrid mmWave massive MIMO
Hybrid analog-digital (HAD) architecture is widely adopted in practical millimeter wave
(mmWave) massive multiple-input multiple-output (MIMO) systems to reduce hardware cost …
(mmWave) massive multiple-input multiple-output (MIMO) systems to reduce hardware cost …
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 …
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 …
Parametric sparse channel estimation using long short-term memory for mmwave massive mimo systems
Millimeter-wave (mmWave) communications will play an important role in 5G and 6G
communication systems as a means to support extremely high data rates. One main …
communication systems as a means to support extremely high data rates. One main …
Recurrent neural network and federated learning based channel estimation approach in mmWave massive MIMO systems
So far, various data‐driven approaches have been presented to obtain channel state
information (CSI) in millimeter wave multiple‐input‐multiple‐output wireless networks. In …
information (CSI) in millimeter wave multiple‐input‐multiple‐output wireless networks. In …
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 …