ShuffleNet-inspired lightweight neural network design for automatic modulation classification methods in ubiquitous IoT cyber–physical systems
J Yin, L Guo, W Jiang, S Hong, J Yang - Computer Communications, 2021 - Elsevier
Automatic modulation classification (AMC) is one of the most important technologies of
cognitive radios and ubiquitous internet of things (IoT) cyber–physical systems, and it can be …
cognitive radios and ubiquitous internet of things (IoT) cyber–physical systems, and it can be …
A hierarchical classification head based convolutional gated deep neural network for automatic modulation classification
Automatic modulation classification (AMC) identifies a received signal's modulation scheme
without prior knowledge of the intercepted signal, which enables significant applications in …
without prior knowledge of the intercepted signal, which enables significant applications in …
Mcformer: A transformer based deep neural network for automatic modulation classification
S Hamidi-Rad, S Jain - 2021 IEEE Global Communications …, 2021 - ieeexplore.ieee.org
In this paper, we propose MCformer-a novel deep neural network for the automatic
modulation classification task of complex-valued raw radio signals. MCformer architecture …
modulation classification task of complex-valued raw radio signals. MCformer architecture …
Gated recurrent unit neural networks for automatic modulation classification with resource-constrained end-devices
The continuous increase in the number of mobile and Internet of Things (IoT) devices, as
well as in the wireless data traffic they generate, represents an essential challenge in terms …
well as in the wireless data traffic they generate, represents an essential challenge in terms …
Moe-amc: Enhancing automatic modulation classification performance using mixture-of-experts
J Gao, Q Cao, Y Chen - arXiv preprint arXiv:2312.02298, 2023 - arxiv.org
Automatic Modulation Classification (AMC) plays a vital role in time series analysis, such as
signal classification and identification within wireless communications. Deep learning-based …
signal classification and identification within wireless communications. Deep learning-based …
Automatic modulation classification using ResNeXt-GRU with deep feature fusion
With the integrated design and application of radar, communication, and electronic
reconnaissance, automatic modulation classification (AMC) is becoming increasingly …
reconnaissance, automatic modulation classification (AMC) is becoming increasingly …
Robust automatic modulation classification in low signal to noise ratio
In a non-cooperative communication environment, automatic modulation classification
(AMC) is an essential technology for analyzing signals and classifying different kinds of …
(AMC) is an essential technology for analyzing signals and classifying different kinds of …
Multi-task learning for generalized automatic modulation classification under non-Gaussian noise with varying SNR conditions
Automatic modulation classification (AMC) is a critical algorithm for the identification of
modulation types so as to enable more accurate demodulation in the non-cooperative …
modulation types so as to enable more accurate demodulation in the non-cooperative …
Attentive siamese networks for automatic modulation classification based on multitiming constellation diagrams
Y Mao, YY Dong, T Sun, X Rao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Automatic modulation classification (AMC) is an essential part in a cognitive radio receiver.
Benefited from the discriminative constellation characteristics among most modulations …
Benefited from the discriminative constellation characteristics among most modulations …
VT-MCNet: High-Accuracy Automatic Modulation Classification Model Based on Vision Transformer
Cognitive radio networks' evolution hinges significantly on the use of automatic modulation
classification (AMC). However, existing research reveals limitations in attaining high AMC …
classification (AMC). However, existing research reveals limitations in attaining high AMC …