Weighted spectral efficiency optimization for hybrid beamforming in multiuser massive MIMO-OFDM systems
J Du, W Xu, C Zhao… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
In this article, we consider hybrid beamforming designs for multiuser massive multiple-input
multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems. Aiming …
multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems. Aiming …
Deterministic annealing for hybrid beamforming design in multi-cell mu-mimo systems
This work deals with hybrid beamforming (HBF) for the MIMO Interfering Broadcast Channel
(IBC), ie the Multi-Input Multi-Output (MIMO) Multi-User (MU) Multi-Cell downlink channel …
(IBC), ie the Multi-Input Multi-Output (MIMO) Multi-User (MU) Multi-Cell downlink channel …
Joint User Scheduling and Resource Allocation in Distributed MIMO Systems with Multi-Carriers
Y Bu, J Zong, X Xia, Y Liu, F Yang, D Wang - Electronics, 2022 - mdpi.com
Compared with the traditional collocated multi-input multi-output system (C-MIMO),
distributed MIMO (D-MIMO) systems have the advantage of higher throughput and coverage …
distributed MIMO (D-MIMO) systems have the advantage of higher throughput and coverage …
On the performance of randomly directional beamforming between line-of-sight and rich scattering channels
In this paper, the performance of random beamforming (RBF) which requires only partial
channel state information (CSI) feedback is investigated for millimeter-wave (mmwave) …
channel state information (CSI) feedback is investigated for millimeter-wave (mmwave) …
Machine learning-based beamforming in two-user MISO interference channels
As the demand for data rate increases, interference management becomes more important,
especially in small cell environment of emerging wireless communication systems. In this …
especially in small cell environment of emerging wireless communication systems. In this …
D2BF—Data-Driven Beamforming in MU-MIMO with Channel Estimation Uncertainty
Accurate estimation of Channel State Information (CSI) is essential to design MU-MIMO
beamforming. However, errors in CSI estimation are inevitable in practice. State-of-the-art …
beamforming. However, errors in CSI estimation are inevitable in practice. State-of-the-art …
Multitask deep learning-based multiuser hybrid beamforming for mm-wave orthogonal frequency division multiple access systems
Multiuser hybrid beamforming of a wideband millimeter-wave (mm-wave) system is a
complex combinatorial optimization problem. It not only needs large training data, but also …
complex combinatorial optimization problem. It not only needs large training data, but also …
Deep reinforcement learning based joint active and passive beamforming design for RIS-assisted MISO systems
Owing to the unique advantages of low cost and controllability, reconfigurable intelligent
surface (RIS) is a promising candidate to address the blockage issue in millimeter wave …
surface (RIS) is a promising candidate to address the blockage issue in millimeter wave …
Deep learning-powered beamforming for 5G massive MIMO Systems
In this study, a ResNeSt-based deep learning approach to beamforming for 5G massive
multiple-input multiple-output (MIMO) systems is presented. The ResNeSt-based deep …
multiple-input multiple-output (MIMO) systems is presented. The ResNeSt-based deep …
Deep reinforcement learning for distributed dynamic MISO downlink-beamforming coordination
We consider a homogeneous cellular network where a multi-antenna base station (BS) in
each cell transmits messages to its intended user over a common frequency band. To …
each cell transmits messages to its intended user over a common frequency band. To …