[PDF] arxiv.org

Deep learning for TDD and FDD massive MIMO: Mapping channels in space and frequency

M Alrabeiah, A Alkhateeb - 2019 53rd asilomar conference on …, 2019 - ieeexplore.ieee.org
Can we map the channels at one set of antennas and one frequency band to the channels at
another set of antennas-possibly at a different location and a different frequency band? If this …
被引用次数：184 相关文章 所有 6 个版本
[PDF] arxiv.org

CAnet: Uplink-aided downlink channel acquisition in FDD massive MIMO using deep learning

J Guo, CK Wen, S Jin - IEEE Transactions on Communications, 2021 - ieeexplore.ieee.org
In frequency-division duplexing systems, the downlink channel state information (CSI)
acquisition scheme leads to high training and feedback overhead. In this work, we propose …
被引用次数：41 相关文章 所有 3 个版本
[PDF] arxiv.org

Enabling FDD massive MIMO through deep learning-based channel prediction

M Arnold, S Dörner, S Cammerer, S Yan… - arXiv preprint arXiv …, 2019 - arxiv.org
A major obstacle for widespread deployment of frequency division duplex (FDD)-based
Massive multiple-input multiple-output (MIMO) communications is the large signaling …
被引用次数：57 相关文章 所有 2 个版本
[PDF] arxiv.org

Deep learning-based antenna selection and CSI extrapolation in massive MIMO systems

B Lin, F Gao, S Zhang, T Zhou… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A critical bottleneck of massive multiple-input multiple-output (MIMO) system is the huge
training overhead caused by downlink transmission, like channel estimation, downlink …
被引用次数：38 相关文章 所有 7 个版本
[PDF] ieee.org

Deep learning-based downlink channel prediction for FDD massive MIMO system

Y Yang, F Gao, GY Li, M Jian - IEEE Communications Letters, 2019 - ieeexplore.ieee.org
In a frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO)
system, the acquisition of downlink channel state information (CSI) at base station (BS) is a …
被引用次数：184 相关文章 所有 5 个版本
[PDF] ieee.org

Deep learning for massive MIMO with 1-bit ADCs: When more antennas need fewer pilots

Y Zhang, M Alrabeiah… - IEEE Wireless …, 2020 - ieeexplore.ieee.org
This letter considers uplink massive MIMO systems with 1-bit analog-to-digital converters
(ADCs) and develops a deep-learning based channel estimation framework. In this …
被引用次数：83 相关文章 所有 7 个版本
[PDF] arxiv.org

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 …
被引用次数：38 相关文章 所有 3 个版本
[PDF] ieee.org

Power allocation in cell-free massive MIMO: A deep learning method

Y Zhao, IG Niemegeers, SH De Groot - IEEE Access, 2020 - ieeexplore.ieee.org
Massive multiple-input multiple-output (MIMO) is a key technology in 5G. It enables multiple
users to be served in the same time-frequency block through precoding or beamforming …
被引用次数：85 相关文章 所有 4 个版本
[PDF] arxiv.org

Deep learning-based CSI feedback and cooperative recovery in massive MIMO

J Guo, X Yang, CK Wen, S Jin, GY Li - arXiv preprint arXiv:2003.03303, 2020 - arxiv.org
In this paper, the correlation between nearby user equipment (UE) is exploited, and a deep
learning-based channel state information (CSI) feedback and cooperative recovery …
被引用次数：47 相关文章
[PDF] arxiv.org

Deep learning for UL/DL channel calibration in generic massive MIMO systems

C Huang, GC Alexandropoulos… - ICC 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
One of the fundamental challenges to realize massive Multiple-Input Multiple-Output (MIMO)
communications is the accurate acquisition of channel state information for a plurality of …
被引用次数：62 相关文章 所有 12 个版本