Hybrid knowledge-data driven channel semantic acquisition and beamforming for cell-free massive MIMO

Z Gao, S Liu, Y Su, Z Li, D Zheng - IEEE Journal of Selected …, 2023 - ieeexplore.ieee.org
This article focuses on advancing outdoor wireless systems to better support ubiquitous
extended reality (XR) applications, and close the gap with current indoor wireless …

Decentralized beamforming for cell-free massive MIMO with unsupervised learning

H Hojatian, J Nadal, JF Frigon… - IEEE Communications …, 2022 - ieeexplore.ieee.org
Cell-free massive MIMO (CF-mMIMO) systems represent a promising approach to increase
the spectral efficiency of wireless communication systems. However, near-optimal …

Unsupervised deep learning for massive MIMO hybrid beamforming

H Hojatian, J Nadal, JF Frigon… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
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 …

Deep learning based beam training for extremely large-scale massive MIMO in near-field domain

W Liu, H Ren, C Pan, J Wang - IEEE Communications Letters, 2022 - ieeexplore.ieee.org
Extremely large-scale massive multiple-input-multiple-output (XL-MIMO) is regarded as a
promising technology for next-generation communication systems. In order to enhance the …

Mixed-timescale deep-unfolding for joint channel estimation and hybrid beamforming

K Kang, Q Hu, Y Cai, G Yu, J Hoydis… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
In massive multiple-input multiple-output (MIMO) systems, hybrid analog-digital
beamforming is an essential technique for exploiting the potential array gain without using a …

Data-driven deep learning based hybrid beamforming for aerial massive MIMO-OFDM systems with implicit CSI

Z Gao, M Wu, C Hu, F Gao, G Wen… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
In an aerial hybrid massive multiple-input multiple-output (MIMO) and orthogonal frequency
division multiplexing (OFDM) system, how to design a spectral-efficient broadband multi …

Federated learning for hybrid beamforming in mm-wave massive MIMO

AM Elbir, S Coleri - IEEE Communications Letters, 2020 - ieeexplore.ieee.org
Machine learning for hybrid beamforming has been extensively studied by using centralized
machine learning (CML) techniques, which require the training of a global model with a …

Intelligent analog beam selection and beamspace channel tracking in THz massive MIMO with lens antenna array

H Zarini, MR Mili, M Rasti, S Andreev… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Beamspace multiple-input-multiple-output (MIMO) as a green technology can efficiently
substitute for the conventional massive MIMO, provided that the beamspace channel is …

Flexible unsupervised learning for massive MIMO subarray hybrid beamforming

H Hojatian, J Nadal, JF Frigon… - … 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
Hybrid beamforming is a promising technology to improve the energy efficiency of massive
MIMO systems. In particular, subarray hybrid beamforming can further decrease power …

Federated learning for precoding design in cell-free massive mimo systems

D Wang, M Tao, X Zeng, J Liang - IEEE Open Journal of the …, 2023 - ieeexplore.ieee.org
Cell-free massive MIMO precoding leverages the large number of antennas and dense
access point (AP) deployment to concurrently serve multiple users in a wide coverage area …