Deep learning based channel code recognition using TextCNN
Deep Learning based Channel Code Recognition using TextCNN Page 1 Deep Learning
based Channel Code Recognition using TextCNN Xiongfei Qin1, Shengliang Peng1∗, Xi …
based Channel Code Recognition using TextCNN Xiongfei Qin1, Shengliang Peng1∗, Xi …
High-performance deep learning classification for radio signals
AJ Uppal, M Hegarty, W Haftel… - 2019 53rd Asilomar …, 2019 - ieeexplore.ieee.org
The ability to classify different types of signal modulations in radio transmissions is an
important task with applications in defense, networking, and communications. This process …
important task with applications in defense, networking, and communications. This process …
Convolutional neural networks for automatic cognitive radio waveform recognition
M Zhang, M Diao, L Guo - IEEE access, 2017 - ieeexplore.ieee.org
Cognitive radio technology is an important branch in the field of wireless communication,
and automatic identification is a major part of cognitive radio technology. Convolutional …
and automatic identification is a major part of cognitive radio technology. Convolutional …
Deep learning-enabled real-time recognition of wireless signals
C Gravelle, T Morehouse, R Zhou - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
In this demonstration, we perform a software defined radio (SDR) prototype of recognizing
wireless signals in real-time. Convolutional Neural Network (CNN), a deep learning …
wireless signals in real-time. Convolutional Neural Network (CNN), a deep learning …
Deep gated recurrent unit convolution network for radio signal recognition
R Li, J Hu, S Yang - 2019 IEEE 19th International Conference …, 2019 - ieeexplore.ieee.org
This paper proposes a Deep Gated Recurrent Unit (GRU) Convolution Network for feature
extraction and classification of radio signals. First, a set of 1-D filters are constructed to …
extraction and classification of radio signals. First, a set of 1-D filters are constructed to …
Deep learning for spectrum sensing in cognitive radio
The detection of primary user signals is essential for optimum utilization of a spectrum by
secondary users in cognitive radio (CR). The conventional spectrum sensing schemes have …
secondary users in cognitive radio (CR). The conventional spectrum sensing schemes have …
Cellular signal identification using convolutional neural networks: AWGN and Rayleigh fading channels
H Xia, K Alshathri, VB Lawrence… - 2019 IEEE …, 2019 - ieeexplore.ieee.org
Spectrum awareness is crucial in wireless communications systems for dynamic network
environments. It is required for spectrum resource management, adaptive transmissions …
environments. It is required for spectrum resource management, adaptive transmissions …
Identification of ISM band signals using deep learning
Spectrum awareness is now becoming more and more important in recent years, which can
be utilized in areas like spectrum resource allocation, spectrum management, inference …
be utilized in areas like spectrum resource allocation, spectrum management, inference …
DeepRx: Fully convolutional deep learning receiver
Deep learning has solved many problems that are out of reach of heuristic algorithms. It has
also been successfully applied in wireless communications, even though the current radio …
also been successfully applied in wireless communications, even though the current radio …
Classifying wireless signal modulation sorting using convolutional neural network
Deep learning has recently been used for this issue with superior results in automatic
modulation classification. Previous studies state that it is challenging to categorize a variety …
modulation classification. Previous studies state that it is challenging to categorize a variety …