# Wireless Signal Modulation Classification

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/wireless-signal-modulation-classification/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the application of deep learning techniques for wireless signal classification, including modulation classification, channel estimation, RF fingerprinting, and spectrum monitoring in cognitive radios. The papers explore the opportunities and challenges of using deep learning in wireless communications and physical layer signal processing. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t12131 |
| Works | 19 |

## Topic papers all

Showing 15 of 19.

- [Contour Stella Image and Deep Learning for Signal Recognition in the Physical Layer](https://scholariq.org/papers/contour-stella-image-and-deep-learning-for-signal-recognition-in-the-physical/)
- [An Improved Neural Network Pruning Technology for Automatic Modulation Classification in Edge Devices](https://scholariq.org/papers/an-improved-neural-network-pruning-technology-for-automatic-modulation/)
- [Complex-Valued Networks for Automatic Modulation Classification](https://scholariq.org/papers/complex-valued-networks-for-automatic-modulation-classification/)
- [Automatic Modulation Classification Using CNN-LSTM Based Dual-Stream Structure](https://scholariq.org/papers/automatic-modulation-classification-using-cnn-lstm-based-dual-stream-structure/)
- [Adversarial Attacks in Modulation Recognition With Convolutional Neural Networks](https://scholariq.org/papers/adversarial-attacks-in-modulation-recognition-with-convolutional-neural-networks/)
- [Automatic Modulation Classification Using Convolutional Neural Network With Features Fusion of SPWVD and BJD](https://scholariq.org/papers/automatic-modulation-classification-using-convolutional-neural-network-with/)
- [Digital Signal Modulation Classification With Data Augmentation Using Generative Adversarial Nets in Cognitive Radio Networks](https://scholariq.org/papers/digital-signal-modulation-classification-with-data-augmentation-using-generative/)
- [The individual identification method of wireless device based on dimensionality reduction and machine learning](https://scholariq.org/papers/the-individual-identification-method-of-wireless-device-based-on-dimensionality/)
- [Zero-Bias Deep Learning for Accurate Identification of Internet of Things (IoT) Devices](https://scholariq.org/papers/zero-bias-deep-learning-for-accurate-identification-of-internet-of-things-iot/)
- [Class-Incremental Learning for Wireless Device Identification in IoT](https://scholariq.org/papers/class-incremental-learning-for-wireless-device-identification-in-iot/)
- [RF-Enabled Deep-Learning-Assisted Drone Detection and Identification: An End-to-End Approach](https://scholariq.org/papers/rf-enabled-deep-learning-assisted-drone-detection-and-identification-an-end-to/)
- [Radar HRRP recognition based on discriminant deep autoencoders with small training data size](https://scholariq.org/papers/radar-hrrp-recognition-based-on-discriminant-deep-autoencoders-with-small/)
- [A Survey of Applications of Deep Learning in Radio Signal Modulation Recognition](https://scholariq.org/papers/a-survey-of-applications-of-deep-learning-in-radio-signal-modulation-recognition/)
- [Research on Intrusion Detection Based on Improved DBN-ELM](https://scholariq.org/papers/research-on-intrusion-detection-based-on-improved-dbn-elm/)
- [Noise-Tolerant, Deep-Learning-Based Radio Identification with Logarithmic Power Spectrum](https://scholariq.org/papers/noise-tolerant-deep-learning-based-radio-identification-with-logarithmic-power/)

## Topic primary papers

- [Contour Stella Image and Deep Learning for Signal Recognition in the Physical Layer](https://scholariq.org/papers/contour-stella-image-and-deep-learning-for-signal-recognition-in-the-physical/)
- [An Improved Neural Network Pruning Technology for Automatic Modulation Classification in Edge Devices](https://scholariq.org/papers/an-improved-neural-network-pruning-technology-for-automatic-modulation/)
- [Complex-Valued Networks for Automatic Modulation Classification](https://scholariq.org/papers/complex-valued-networks-for-automatic-modulation-classification/)
- [Automatic Modulation Classification Using CNN-LSTM Based Dual-Stream Structure](https://scholariq.org/papers/automatic-modulation-classification-using-cnn-lstm-based-dual-stream-structure/)
- [Automatic Modulation Classification Using Convolutional Neural Network With Features Fusion of SPWVD and BJD](https://scholariq.org/papers/automatic-modulation-classification-using-convolutional-neural-network-with/)
- [Digital Signal Modulation Classification With Data Augmentation Using Generative Adversarial Nets in Cognitive Radio Networks](https://scholariq.org/papers/digital-signal-modulation-classification-with-data-augmentation-using-generative/)
- [The individual identification method of wireless device based on dimensionality reduction and machine learning](https://scholariq.org/papers/the-individual-identification-method-of-wireless-device-based-on-dimensionality/)
- [Zero-Bias Deep Learning for Accurate Identification of Internet of Things (IoT) Devices](https://scholariq.org/papers/zero-bias-deep-learning-for-accurate-identification-of-internet-of-things-iot/)
- [Class-Incremental Learning for Wireless Device Identification in IoT](https://scholariq.org/papers/class-incremental-learning-for-wireless-device-identification-in-iot/)
- [RF-Enabled Deep-Learning-Assisted Drone Detection and Identification: An End-to-End Approach](https://scholariq.org/papers/rf-enabled-deep-learning-assisted-drone-detection-and-identification-an-end-to/)
- [A Survey of Applications of Deep Learning in Radio Signal Modulation Recognition](https://scholariq.org/papers/a-survey-of-applications-of-deep-learning-in-radio-signal-modulation-recognition/)
- [Noise-Tolerant, Deep-Learning-Based Radio Identification with Logarithmic Power Spectrum](https://scholariq.org/papers/noise-tolerant-deep-learning-based-radio-identification-with-logarithmic-power/)
- [Towards recurrent neural network with multi-path feature fusion for signal modulation recognition](https://scholariq.org/papers/towards-recurrent-neural-network-with-multi-path-feature-fusion-for-signal/)
- [Blind modulation classification based on MLP and PNN](https://scholariq.org/papers/blind-modulation-classification-based-on-mlp-and-pnn/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.