C She, C Sun, Z Gu, Y Li, C Yang… - Proceedings of the …, 2021 - ieeexplore.ieee.org
As one of the key communication scenarios in the fifth-generation and also the sixth- generation (6G) mobile communication networks, ultrareliable and low-latency …
P Jiang, CK Wen, S Jin, GY Li - IEEE Journal on Selected Areas …, 2022 - ieeexplore.ieee.org
Video conferencing has become a popular mode of meeting despite consuming considerable communication resources. Conventional video compression causes resolution …
Many performance gains achieved by massive multiple-input and multiple-output depend on the accuracy of the downlink channel state information (CSI) at the transmitter (base station) …
This paper deals with the use of emerging deep learning techniques in future wireless communication networks. It will be shown that the data-driven approaches should not …
For 6G in 2030 and beyond, key performance metrics long for terabit-per-second, one-tenth of millisecond latency with zero jitter, millimeter-preci-sion sensing and positioning, and …
Z Qin, H Ye, GY Li, BHF Juang - IEEE Wireless …, 2019 - ieeexplore.ieee.org
DL has shown great potential to revolutionize communication systems. This article provides an overview of the recent advancements in DL-based physical layer communications. DL …
With a ten-year horizon from concept to reality, it is time now to start thinking about what will the sixth-generation (6G) mobile communications be on the eve of the fifth-generation (5G) …
H He, CK Wen, S Jin, GY Li - IEEE Transactions on Signal …, 2020 - ieeexplore.ieee.org
In this paper, we investigate the model-driven deep learning (DL) for MIMO detection. In particular, the MIMO detector is specially designed by unfolding an iterative algorithm and …
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from “connected things” to “connected intelligence”, featured by ultra high density, large-scale …