On the road to 6G: Visions, requirements, key technologies, and testbeds
Fifth generation (5G) mobile communication systems have entered the stage of commercial
deployment, providing users with new services, improved user experiences as well as a host …
deployment, providing users with new services, improved user experiences as well as a host …
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 …
White paper on broadband connectivity in 6G
This white paper explores the road to implementing broadband connectivity in future 6G
wireless systems. Different categories of use cases are considered, from extreme capacity …
wireless systems. Different categories of use cases are considered, from extreme capacity …
Deep channel learning for large intelligent surfaces aided mm-wave massive MIMO systems
AM Elbir, A Papazafeiropoulos… - IEEE Wireless …, 2020 - ieeexplore.ieee.org
This letter presents the first work introducing a deep learning (DL) framework for channel
estimation in large intelligent surface (LIS) assisted massive MIMO (multiple-input multiple …
estimation in large intelligent surface (LIS) assisted massive MIMO (multiple-input multiple …
Federated learning for channel estimation in conventional and RIS-assisted massive MIMO
Machine learning (ML) has attracted a great research interest for physical layer design
problems, such as channel estimation, thanks to its low complexity and robustness. Channel …
problems, such as channel estimation, thanks to its low complexity and robustness. Channel …
Transfer learning and meta learning-based fast downlink beamforming adaptation
This article studies fast adaptive beamforming optimization for the signal-to-interference-plus-
noise ratio balancing problem in a multiuser multiple-input single-output downlink system …
noise ratio balancing problem in a multiuser multiple-input single-output downlink system …
A survey of millimeter-wave communication: Physical-layer technology specifications and enabling transmission technologies
Millimeter-wave (mmWave) frequency bands, which offer abundant underutilized spectral
resources, have been explored and exploited in the past several years to meet the …
resources, have been explored and exploited in the past several years to meet the …
Enabling AI in future wireless networks: A data life cycle perspective
Recent years have seen rapid deployment of mobile computing and Internet of Things (IoT)
networks, which can be mostly attributed to the increasing communication and sensing …
networks, which can be mostly attributed to the increasing communication and sensing …
Federated learning for automatic modulation classification under class imbalance and varying noise condition
Automatic modulation classification (AMC) is a promising technology for identifying
modulation types, and deep learning (DL)-based AMC is one of its main research directions …
modulation types, and deep learning (DL)-based AMC is one of its main research directions …
Unsupervised deep learning for massive MIMO hybrid beamforming
Hybrid beamforming is a promising technique to reduce the complexity and cost of massive
multiple-input multiple-output (MIMO) systems while providing high data rate. However, the …
multiple-input multiple-output (MIMO) systems while providing high data rate. However, the …