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 …
A major obstacle for widespread deployment of frequency division duplex (FDD)-based Massive multiple-input multiple-output (MIMO) communications is the large signaling …
A critical bottleneck of massive multiple-input multiple-output (MIMO) system is the huge training overhead caused by downlink transmission, like channel estimation, downlink …
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 …
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 …
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 …
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 …
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 …
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 …