Deep learning based automatic modulation recognition: Models, datasets, and challenges
F Zhang, C Luo, J Xu, Y Luo, FC Zheng - Digital Signal Processing, 2022 - Elsevier
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 …
Automatic modulation recognition based on adaptive attention mechanism and ResNeXt WSL model
Z Liang, M Tao, L Wang, J Su… - IEEE Communications …, 2021 - ieeexplore.ieee.org
Automatic modulation recognition (AMR) plays an important role in modern wireless
communication. In this letter, a novel framework for AMR is proposed. The ResNeXt network …
communication. In this letter, a novel framework for AMR is proposed. The ResNeXt network …
Signal processing-based deep learning for blind symbol decoding and modulation classification
Blindly decoding a signal requires estimating its unknown transmit parameters,
compensating for the wireless channel impairments, and identifying the modulation type …
compensating for the wireless channel impairments, and identifying the modulation type …
Rml22: Realistic dataset generation for wireless modulation classification
V Sathyanarayanan, P Gerstoft… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Application of Deep learning (DL) to modulation classification has shown significant
performance improvements. The focus has been model centric, where newer architectures …
performance improvements. The focus has been model centric, where newer architectures …
Machine learning empowered spectrum sensing under a sub-sampling framework
Compressive sensing (CS) is a technique frequently adopted in wireless communications.
By utilizing CS, a receiver could sense the state of channels with sub-Nyquist analog to …
By utilizing CS, a receiver could sense the state of channels with sub-Nyquist analog to …
An advancing temporal convolutional network for 5G latency services via automatic modulation recognition
Automatic modulation recognition (AMR) has received significant attention since its decisive
factor for modern non-cooperative communication systems. Meanwhile, the existing works …
factor for modern non-cooperative communication systems. Meanwhile, the existing works …
Toward the Automatic Modulation Classification With Adaptive Wavelet Network
With the evolutionary development of modern communications technology, automatic
modulation classification (AMC) has played an increasing role in the complex wireless …
modulation classification (AMC) has played an increasing role in the complex wireless …
Neural decoding with optimization of node activations
E Nachmani, Y Be'ery - IEEE Communications Letters, 2022 - ieeexplore.ieee.org
The problem of maximum likelihood decoding with a neural decoder for error-correcting
code is considered. It is shown that the neural decoder can be improved with two novel loss …
code is considered. It is shown that the neural decoder can be improved with two novel loss …
Autoregressive belief propagation for decoding block codes
E Nachmani, L Wolf - arXiv preprint arXiv:2103.11780, 2021 - arxiv.org
We revisit recent methods that employ graph neural networks for decoding error correcting
codes and employ messages that are computed in an autoregressive manner. The outgoing …
codes and employ messages that are computed in an autoregressive manner. The outgoing …
Data-Driven Subsampling in the Presence of an Adversarial Actor
Deep learning based automatic modulation classification (AMC) has received significant
attention owing to its potential applications in both military and civilian use cases. Recently …
attention owing to its potential applications in both military and civilian use cases. Recently …