A deep learning and geospatial data-based channel estimation technique for hybrid massive MIMO systems
X Zhu, A Koc, R Morawski, T Le-Ngoc - IEEE Access, 2021 - ieeexplore.ieee.org
This paper presents a novel channel estimation technique for the multi-user massive
multiple-input multiple-output (MU-mMIMO) systems using angular-based hybrid precoding …
multiple-input multiple-output (MU-mMIMO) systems using angular-based hybrid precoding …
On the performance of reconfigurable intelligent surface-aided cell-free massive MIMO uplink
The uplink of a reconfigurable intelligent surfaces (RIS)-aided cell-free massive multiple-
input multiple-output (MIMO) system is analyzed, where the channel state information (CSI) …
input multiple-output (MIMO) system is analyzed, where the channel state information (CSI) …
Deep learning for direct hybrid precoding in millimeter wave massive MIMO systems
X Li, A Alkhateeb - 2019 53rd Asilomar Conference on Signals …, 2019 - ieeexplore.ieee.org
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 …
auto-precoder network jointly senses the millimeter wave (mmWave) channel and designs …
Reconfigurable intelligent surface-assisted cell-free massive MIMO systems over spatially-correlated channels
Cell-Free Massive multiple-input multiple-output (MIMO) and reconfigurable intelligent
surface (RIS) are two promising technologies for application to beyond-5G networks. This …
surface (RIS) are two promising technologies for application to beyond-5G networks. This …
Statistical CSI-based transmission design for reconfigurable intelligent surface-aided massive MIMO systems with hardware impairments
We consider a reconfigurable intelligent surface (RIS)-aided massive multi-user multiple-
input multiple-output (MIMO) communication system with transceiver hardware impairments …
input multiple-output (MIMO) communication system with transceiver hardware impairments …
Hybrid precoding for multiuser millimeter wave massive MIMO systems: A deep learning approach
AM Elbir, AK Papazafeiropoulos - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
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 …
hybrid precoding is a crucial task to lower the complexity and cost while achieving a …
RIS-aided cell-free massive MIMO systems for 6G: Fundamentals, system design, and applications
An introduction of intelligent interconnectivity for people and things has posed higher
demands and more challenges for sixth-generation (6G) networks, such as high spectral …
demands and more challenges for sixth-generation (6G) networks, such as high spectral …
Is RIS-aided massive MIMO promising with ZF detectors and imperfect CSI?
This paper provides a theoretical framework for understanding the performance of
reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) …
reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) …
Performance analysis of RIS-assisted cell-free massive MIMO systems with transceiver hardware impairments
Integrating reconfigurable intelligent surface (RIS) into cell-free massive multiple-input
multiple-output (MIMO) is a promising approach to enhance the coverage quality, spectral …
multiple-output (MIMO) is a promising approach to enhance the coverage quality, spectral …
Unsupervised deep learning for massive MIMO hybrid beamforming
Hybrid beamforming is a promising technique to reduce the complexity and cost of massive
multiple-input multiple-output (MIMO) systems while providing high data rate. However, the …
multiple-input multiple-output (MIMO) systems while providing high data rate. However, the …