Machine learning in beyond 5G/6G networks—State-of-the-art and future trends
Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
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 …
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-based implicit CSI feedback in massive MIMO
Massive multiple-input multiple-output can obtain more performance gain by exploiting the
downlink channel state information (CSI) at the base station (BS). Therefore, studying CSI …
downlink channel state information (CSI) at the base station (BS). Therefore, studying CSI …
ChannelGAN: Deep learning-based channel modeling and generating
H Xiao, W Tian, W Liu, J Shen - IEEE Wireless …, 2022 - ieeexplore.ieee.org
The increasing complexity on channel modeling and the cost on collecting plenty of high-
quality wireless channel data have become the main bottlenecks of developing deep …
quality wireless channel data have become the main bottlenecks of developing deep …
Specific emitter identification using adaptive signal feature embedded knowledge graph
Specific emitter identification (SEI) plays an important role in secure Industrial Internet of
Things (IIoT). In recent years, many SEI methods based on machine learning (ML) and deep …
Things (IIoT). In recent years, many SEI methods based on machine learning (ML) and deep …
CAnet: Uplink-aided downlink channel acquisition in FDD massive MIMO using deep learning
In frequency-division duplexing systems, the downlink channel state information (CSI)
acquisition scheme leads to high training and feedback overhead. In this work, we propose …
acquisition scheme leads to high training and feedback overhead. In this work, we propose …
User-centric online gossip training for autoencoder-based CSI feedback
Recently, the autoencoder framework has shown great potential in reducing the feedback
overhead of the downlink channel state information (CSI). In this work, we further find that …
overhead of the downlink channel state information (CSI). In this work, we further find that …
Downlink channel estimation for FDD massive MIMO using conditional generative adversarial networks
B Banerjee, RC Elliott, WA Krzymień… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
For implementation of massive multiple-input multiple-output (MIMO) cellular systems in
frequency division duplex (FDD) mode, accurate estimation of downlink channel state …
frequency division duplex (FDD) mode, accurate estimation of downlink channel state …
A comprehensive survey on 6G and beyond: Enabling technologies, opportunities of machine learning and challenges
Multiple nations are now in the process of launching 5G mobile networks. All of the telecoms
industry has been revolutionized by the concept of 5G networks. Since late 2018 …
industry has been revolutionized by the concept of 5G networks. Since late 2018 …