A tutorial on environment-aware communications via channel knowledge map for 6G

Y Zeng, J Chen, J Xu, D Wu, X Xu, S **… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Sixth-generation (6G) mobile communication networks are expected to have dense
infrastructures, large antenna size, wide bandwidth, cost-effective hardware, diversified …

A new 5G radio evolution towards 5G-Advanced

J Pang, S Wang, Z Tang, Y Qin, X Tao, X You… - Science China …, 2022 - Springer
The evolution of the fifth-generation (5G) new radio (NR) has progressed swiftly since the
third generation partnership project (3GPP) standardized the first NR version (Release 15) …

Deep learning for mmWave beam and blockage prediction using sub-6 GHz channels

M Alrabeiah, A Alkhateeb - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Predicting the millimeter wave (mmWave) beams and blockages using sub-6 GHz channels
has the potential of enabling mobility and reliability in scalable mmWave systems. Prior work …

Computer vision-aided reconfigurable intelligent surface-based beam tracking: Prototy** and experimental results

M Ouyang, F Gao, Y Wang, S Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this paper, we propose a novel computer vision-based approach to aid reconfigurable
intelligent surface (RIS) for dynamic beam tracking and implement the corresponding …

Passive radar at the roadside unit to configure millimeter wave vehicle-to-infrastructure links

A Ali, N González-Prelcic… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Millimeter wave (mmWave) vehicular channels are highly dynamic, and the communication
link needs to be reconfigured frequently. In this work, we propose to use a passive radar …

MIG median detectors with manifold filter

X Hua, L Peng - Signal Processing, 2021 - Elsevier
In this paper, we propose a class of median-based matrix information geometry (MIG)
detectors with a manifold filter and apply them to signal detection in nonhomogeneous …

Deep learning based channel covariance matrix estimation with user location and scene images

W Xu, F Gao, J Zhang, X Tao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Channel covariance matrix (CCM) is one critical parameter for designing the
communications systems. In this paper, a novel framework of the deep learning (DL) based …

Deep learning based channel extrapolation for large-scale antenna systems: Opportunities, challenges and solutions

S Zhang, Y Liu, F Gao, C **ng, J An… - IEEE Wireless …, 2021 - ieeexplore.ieee.org
With the depletion of spectrum, wireless communication systems turn to exploit large
antenna arrays to achieve the degree of freedom in the space domain, such as millimeter …

PARAMOUNT: Towards generalizable deeP leARning for mmwAve beaM selectiOn using sUb-6GHz chaNnel measuremenTs

K Vuckovic, MB Mashhadi, F Hejazi… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Deep neural networks (DNNs) in the wireless communication domain have been shown to
be hardly generalizable to scenarios where the train and test datasets follow a different …

Deep learning-based link configuration for radar-aided multiuser mmWave vehicle-to-infrastructure communication

A Graff, Y Chen, N González-Prelcic… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Configuring millimeter wave links following a conventional beam training protocol, as the
one proposed in the current cellular standard, introduces a large communication overhead …