Neural network-based fading channel prediction: A comprehensive overview
W Jiang, HD Schotten - IEEE Access, 2019 - ieeexplore.ieee.org
By adapting transmission parameters such as the constellation size, coding rate, and
transmit power to instantaneous channel conditions, adaptive wireless communications can …
transmit power to instantaneous channel conditions, adaptive wireless communications can …
[HTML][HTML] Multimedia communication over cognitive radio networks from QoS/QoE perspective: A comprehensive survey
The stringent requirements of wireless multimedia transmission lead to very high radio
spectrum solicitation. Although the radio spectrum is considered as a scarce resource, the …
spectrum solicitation. Although the radio spectrum is considered as a scarce resource, the …
Data-driven deep learning for automatic modulation recognition in cognitive radios
Automatic modulation recognition (AMR) is an essential and challenging topic in the
development of the cognitive radio (CR), and it is a cornerstone of CR adaptive modulation …
development of the cognitive radio (CR), and it is a cornerstone of CR adaptive modulation …
Deep-learning-based millimeter-wave massive MIMO for hybrid precoding
H Huang, Y Song, J Yang, G Gui… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) has been
regarded to be an emerging solution for the next generation of communications, in which …
regarded to be an emerging solution for the next generation of communications, in which …
Flight delay prediction based on aviation big data and machine learning
Accurate flight delay prediction is fundamental to establish the more efficient airline
business. Recent studies have been focused on applying machine learning methods to …
business. Recent studies have been focused on applying machine learning methods to …
An intrusion detection model based on feature reduction and convolutional neural networks
Y Xiao, C Xing, T Zhang, Z Zhao - IEEE Access, 2019 - ieeexplore.ieee.org
With the popularity and development of network technology and the Internet, intrusion
detection systems (IDSs), which can identify attacks, have been developed. Traditional …
detection systems (IDSs), which can identify attacks, have been developed. Traditional …
Fast beamforming design via deep learning
H Huang, Y Peng, J Yang, W Xia… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Beamforming is considered as one of the most important techniques for designing advanced
multiple-input and multiple-output (MIMO) systems. Among existing design criterions, sum …
multiple-input and multiple-output (MIMO) systems. Among existing design criterions, sum …
Complex-valued networks for automatic modulation classification
Deep learning (DL) has been recognized as an effective solution for automatic modulation
classification (AMC). However, most recent DL based AMC works are based on real-valued …
classification (AMC). However, most recent DL based AMC works are based on real-valued …
Behavioral modeling and linearization of wideband RF power amplifiers using BiLSTM networks for 5G wireless systems
Characterization and linearization of RF power amplifiers (PAs) are key issues of fifth-
generation wireless communication systems, especially when high peak-to-average ratio …
generation wireless communication systems, especially when high peak-to-average ratio …
Unsupervised learning-based fast beamforming design for downlink MIMO
In the downlink transmission scenario, power allocation and beamforming design at the
transmitter are essential when using multiple antenna arrays. This paper considers a …
transmitter are essential when using multiple antenna arrays. This paper considers a …