A Real-Time Modulation Recognition System Based on Software-Defined Radio and Multi-Skip Residual Neural Network
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3043588
Abstract: Communication signal modulation recognition has important research value in the fields of cognitive electronic warfare, communication countermeasures and non-collaborative communication. However, traditional signal recognition methods usually suffer some drawbacks, such as low accuracy, poor scalability,… read more here.
Keywords: modulation recognition; real time; multi skip; recognition ... See more keywords
Fully Complex Deep Learning Classifiers for Signal Modulation Recognition in Non-Cooperative Environment
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3151980
Abstract: Deep learning (DL) classifiers have significantly outperformed traditional likelihood-based or feature-based classifiers for signal modulation recognition in non-cooperative environments. However, despite these recent improvements, the conventional DL classifiers still have an unintended problem in handling… read more here.
Keywords: learning classifiers; deep learning; modulation recognition; modulation ... See more keywords
Efficient Residual Shrinkage CNN Denoiser Design for Intelligent Signal Processing: Modulation Recognition, Detection, and Decoding
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal on Selected Areas in Communications"
DOI: 10.1109/jsac.2021.3126074
Abstract: The noises embedded in signals will degrade the signal processing quality. Traditional denoising algorithms might not work in practical systems since the statistical characteristics of noises might not be learned. To address this issue, we… read more here.
Keywords: modulation recognition; denoiser; signal processing; detection decoding ... See more keywords
OAE-EEKNN: An Accurate and Efficient Automatic Modulation Recognition Method for Underwater Acoustic Signals
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3145329
Abstract: The automatic modulation recognition (AMR) enables the receiver to automatically recognize the modulation type of the received signal for achieving correct demodulation. However, the noise and interference in the underwater acoustic channel greatly influence the… read more here.
Keywords: modulation recognition; oae eeknn; modulation; underwater acoustic ... See more keywords
Spectrum Analysis and Convolutional Neural Network for Automatic Modulation Recognition
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Wireless Communications Letters"
DOI: 10.1109/lwc.2019.2900247
Abstract: Recent convolutional neural networks (CNNs)-based image processing methods have proven that CNNs are good at extracting features of spatial data. In this letter, we present a CNN-based modulation recognition framework for the detection of radio… read more here.
Keywords: modulation recognition; spectrum analysis; modulation; radio signals ... See more keywords
Modulation Recognition With Graph Convolutional Network
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Wireless Communications Letters"
DOI: 10.1109/lwc.2019.2963828
Abstract: In most non-cooperative communication systems, modulation recognition is a fundamental and critical technique. Traditional methods of modulation recognition can be categorized as maximum likelihood hypothesis algorithms and pattern recognition algorithms. However, these methods have high… read more here.
Keywords: modulation recognition; graph convolutional; modulation; convolutional network ... See more keywords
Wideband Cyclostationary Signal Processing Using Sparse Subsets of Narrowband Subchannels
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Cognitive Communications and Networking"
DOI: 10.1109/tccn.2018.2790971
Abstract: The problem of signal detection and modulation recognition is addressed in both the blind and nonblind contexts. Many relevant modulation recognition algorithms have been created over the past three decades. The essential engineering tradeoff that… read more here.
Keywords: using sparse; wideband cyclostationary; sparse subsets; cyclostationary signal ... See more keywords
EMD and VMD Empowered Deep Learning for Radio Modulation Recognition
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Cognitive Communications and Networking"
DOI: 10.1109/tccn.2022.3218694
Abstract: Deep learning has been widely exploited in radio modulation recognition in recent years. In this paper, we exploit empirical mode decomposition (EMD) and variational mode decomposition (VMD) in deep learning-based radio modulation recognition. The received… read more here.
Keywords: recognition; modulation recognition; radio modulation; deep learning ... See more keywords
Signal Augmentations Oriented to Modulation Recognition in the Realistic Scenarios
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Communications"
DOI: 10.1109/tcomm.2023.3236379
Abstract: The recent years had witnessed a resurgence on neural network. Many hidden layers were stacked hierarchically to learn the high-level representations. Great performances were achieved by the learned representations. However, this kind of learning models… read more here.
Keywords: recognition; modulation recognition; realistic scenarios; signal augmentations ... See more keywords
An Advancing Temporal Convolutional Network for 5G Latency Services via Automatic Modulation Recognition
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2022.3152522
Abstract: Automatic modulation recognition (AMR) has received significant attention since its decisive factor for modern non-cooperative communication systems. Meanwhile, the existing works on deep learning technique achieve exceptional accuracy; however, these works dissatisfy real-time requirements for… read more here.
Keywords: modulation recognition; latency services; automatic modulation; latency ... See more keywords
Adversarial Attacks in Modulation Recognition With Convolutional Neural Networks
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Reliability"
DOI: 10.1109/tr.2020.3032744
Abstract: Deep learning (DL) models are vulnerable to adversarial attacks, by adding a subtle perturbation which is imperceptible to the human eye, a convolutional neural network (CNN) can lead to erroneous results, which greatly reduces the… read more here.
Keywords: modulation recognition; perturbation; convolutional neural; adversarial attacks ... See more keywords