Adversarial machine learning in wireless communications using RF data: A review
D Adesina, CC Hsieh, YE Sagduyu… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …
complex tasks involved in wireless communications. Supported by recent advances in …
Machine learning for large-scale optimization in 6g wireless networks
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 …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
Enabling large intelligent surfaces with compressive sensing and deep learning
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 …
coverage and rate of future wireless systems. These surfaces comprise massive numbers of …
DeepSense 6G: A large-scale real-world multi-modal sensing and communication dataset
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 …
real-world measurements of co-existing multi-modal sensing and communication data. The …
Overview of deep learning-based CSI feedback in massive MIMO systems
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) …
the accuracy of the downlink channel state information (CSI) at the transmitter (base station) …
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 …
has the potential of enabling mobility and reliability in scalable mmWave systems. Prior work …
Machine learning in the air
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 …
learning (ML) is penetrating every facet of our lives, and transforming research in many …
Millimeter wave fmcw radars for perception, recognition and localization in automotive applications: A survey
MmWave (millimeter wave) Frequency Modulated Continuous Waves (FMCW) RADARs are
sensors based on frequency-modulated electromagnetic which see their environment in 3D …
sensors based on frequency-modulated electromagnetic which see their environment in 3D …
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 …
another set of antennas-possibly at a different location and a different frequency band? If this …
Deep reinforcement learning for intelligent reflecting surfaces: Towards standalone operation
The promising coverage and spectral efficiency gains of intelligent reflecting surfaces (IRSs)
are attracting increasing interest. To adopt these surfaces in practice, however, several …
are attracting increasing interest. To adopt these surfaces in practice, however, several …