Deep learning based automatic modulation recognition: Models, datasets, and challenges
Automatic modulation recognition (AMR) detects the modulation scheme of the received
signals for further signal processing without needing prior information, and provides the …
signals for further signal processing without needing prior information, and provides the …
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 …
Transfer learning for semi-supervised automatic modulation classification in ZF-MIMO systems
Automatic modulation classification (AMC) is an essential technology for the non-
cooperative communication systems, and it is widely applied into various communications …
cooperative communication systems, and it is widely applied into various communications …
Automatic modulation classification for MIMO systems via deep learning and zero-forcing equalization
Automatic modulation classification (AMC) is one of the most critical technologies for non-
cooperative communication systems. Recently, deep learning (DL) based AMC (DL-AMC) …
cooperative communication systems. Recently, deep learning (DL) based AMC (DL-AMC) …
Automatic modulation classification: A deep architecture survey
Automatic modulation classification (AMC), which aims to blindly identify the modulation type
of an incoming signal at the receiver in wireless communication systems, is a fundamental …
of an incoming signal at the receiver in wireless communication systems, is a fundamental …
Deep learning based modulation classification for 5G and beyond wireless systems
The 5G and beyond wireless networks will be more dynamic and heterogeneous, which
needs to work on multistrand waveforms. One of the most significant challenges in such a …
needs to work on multistrand waveforms. One of the most significant challenges in such a …
Deep residual learning-based cognitive model for detection and classification of transmitted signal patterns in 5G smart city networks
Primary user (PU) signal detection or classification is a critical component of cognitive radio
(CR) related wireless communication applications. In CR, the PU detection methods are …
(CR) related wireless communication applications. In CR, the PU detection methods are …
Low-cost convolutional neural network for tomato plant diseases classifiation
S Bensaadi, A Louchene - IAES International Journal of …, 2023 - search.proquest.com
Agriculture is a crucial element to build a strong economy, not only because of its
importance in providing food, but also as a source of raw materials for industry as well as …
importance in providing food, but also as a source of raw materials for industry as well as …
Deep learning techniques for automatic modulation classification: A systematic literature review
Implementation of Automatic modulation classification originated in the military field several
years ago. Threat analysis, surveillance, and welfare where of great concern, thus this urged …
years ago. Threat analysis, surveillance, and welfare where of great concern, thus this urged …
Dendrogram-based Artificial Neural Network modulation classification for dual-hop cooperative relaying communications
This paper contributes to the growing field of Artificial Neural Networks (ANNs) strategies of
Automatic Modulation Identification (AMI) for Cognitive Radio (CR). Traditional AMI-based …
Automatic Modulation Identification (AMI) for Cognitive Radio (CR). Traditional AMI-based …