Big AI models for 6G wireless networks: Opportunities, challenges, and research directions

Z Chen, Z Zhang, Z Yang - IEEE Wireless Communications, 2024 - ieeexplore.ieee.org
Recently, big artificial intelligence models (BAIMs) represented by chatGPT have brought an
incredible revolution. With the pre-trained BAIMs in certain fields, numerous downstream …

Machine learning for large-scale optimization in 6g wireless networks

Y Shi, L Lian, Y Shi, Z Wang, Y Zhou… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
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 …

DeepSense 6G: A large-scale real-world multi-modal sensing and communication dataset

A Alkhateeb, G Charan, T Osman… - IEEE …, 2023 - ieeexplore.ieee.org
This article presents the DeepSense 6G data-set, which is a large-scale dataset based on
real-world measurements of co-existing multi-modal sensing and communication data. The …

Enabling large intelligent surfaces with compressive sensing and deep learning

A Taha, M Alrabeiah, A Alkhateeb - IEEE access, 2021 - ieeexplore.ieee.org
Employing large intelligent surfaces (LISs) is a promising solution for improving the
coverage and rate of future wireless systems. These surfaces comprise massive numbers of …

Overview of deep learning-based CSI feedback in massive MIMO systems

J Guo, CK Wen, S **, GY Li - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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) …

Millimeter wave fmcw radars for perception, recognition and localization in automotive applications: A survey

A Venon, Y Dupuis, P Vasseur… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
MmWave (millimeter wave) Frequency Modulated Continuous Waves (FMCW) RADARs are
sensors based on frequency-modulated electromagnetic which see their environment in 3D …

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 …

Machine learning in the air

D Gündüz, P De Kerret, ND Sidiropoulos… - IEEE Journal on …, 2019 - ieeexplore.ieee.org
Thanks to the recent advances in processing speed, data acquisition and storage, machine
learning (ML) is penetrating every facet of our lives, and transforming research in many …

Intelligent multi-modal sensing-communication integration: Synesthesia of machines

X Cheng, H Zhang, J Zhang, S Gao, S Li… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
In the era of sixth-generation (6G) wireless communications, integrated sensing and
communications (ISAC) is recognized as a promising solution to upgrade the physical …

A tutorial on nyusim: Sub-terahertz and millimeter-wave channel simulator for 5G, 6G and beyond

H Poddar, S Ju, D Shakya… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
With the advancement of wireless communication to sub-terahertz (THz) and millimeter-
wave (mmWave) bands, accurate channel models and simulation tools are becoming …