FocusLab

Before 2022

Y. Wang, J. Wang, W. Zhang, J. Yang and G. Gui, "Deep Learning-Based Cooperative Automatic Modulation Classification Method for MIMO Systems," in IEEE Transactions on Vehicular Technology, vol. 69, no. 4, pp. 4575-4579, April 2020. [Paper][Code]
Y. Wang, G. Gui, H. Gacanin, T. Ohtsuki, O. A. Dobre and H. V. Poor, "An Efficient Specific Emitter Identification Method Based on Complex-Valued Neural Networks and Network Compression," in IEEE Journal on Selected Areas in Communications, vol. 39, no. 8, pp. 2305-2317, Aug. 2021. [Paper][Code]
Y. Wang, G. Gui, H. Gacanin, B. Adebisi, H. Sari and F. Adachi, "Federated Learning for Automatic Modulation Classification Under Class Imbalance and Varying Noise Condition," in IEEE Transactions on Cognitive Communications and Networking, vol. 8, no. 1, pp. 86-96, March 2022.[Paper][Code]
Z. He et al., "Edge Device Identification Based on Federated Learning and Network Traffic Feature Engineering," in IEEE Transactions on Cognitive Communications and Networking, vol. 8, no. 4, pp. 1898-1909, Dec. 2022.[Paper][Code]
J. Ning et al., "Malware Traffic Classification Using Domain Adaptation and Ladder Network for Secure Industrial Internet of Things," in IEEE Internet of Things Journal, vol. 9, no. 18, pp. 17058-17069, 15 Sept.15, 2022.[Paper][Code]
Y. Wang, G. Gui, Y. Lin, H. -C. Wu, C. Yuen and F. Adachi, "Few-Shot Specific Emitter Identification via Deep Metric Ensemble Learning," in IEEE Internet of Things Journal, vol. 9, no. 24, pp. 24980-24994, Dec.15, 2022.[Paper][Code]
J. Yang, Y. Wang, H. Zhao and G. Gui, "MobileNet and Knowledge Distillation-Based Automatic Scenario Recognition Method in Vehicle-to-Vehicle Systems," in IEEE Transactions on Vehicular Technology, vol. 71, no. 10, pp. 11006-11016, Oct. 2022.[Paper][Code]
B. Dong et al., "A Lightweight Decentralized-Learning-Based Automatic Modulation Classification Method for Resource-Constrained Edge Devices," in IEEE Internet of Things Journal, vol. 9, no. 24, pp. 24708-24720, 15 Dec.15, 2022.[Paper][Code]
H. Liu, C. Hao, Y. Peng, Y. Wang, T. Ohtsuki and G. Gui, "An Effective Radio Frequency Signal Classification Method Based on Multi-Task Learning Mechanism," 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall), London, United Kingdom, 2022, pp. 1-5.[Paper][Code]
S. Xu, Z. He, W. Shi, Y. Wang, T. Ohtsuki and G. Guiy, "Cross-Person Activity Recognition Method Using Snapshot Ensemble Learning," 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall), London, United Kingdom, 2022, pp. 1-5.[Paper][Code]
X. Zhang et al., "NAS-AMR: Neural Architecture Search-Based Automatic Modulation Recognition for Integrated Sensing and Communication Systems," in IEEE Transactions on Cognitive Communications and Networking, vol. 8, no. 3, pp. 1374-1386, Sept. 2022.[Paper][Code]

2023

X. Fu et al., "Semi-Supervised Specific Emitter Identification Method Using Metric-Adversarial Training," in IEEE Internet of Things Journal, vol. 10, no. 12, pp. 10778-10789, 15 June15, 2023.[Paper][Code]
C. Liu et al., "A Robust Few-Shot SEI Method Using Class-Reconstruction and Adversarial Training," 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall), London, United Kingdom, 2022, pp. 1-5.[Paper][Code]
Y. Huang, X. Zhang, Y. Wang, D. Jiao, G. Gui and T. Ohtsuki, "NASEI: Neural Architecture Search-Based Specific Emitter Identification Method," 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring), Florence, Italy, 2023, pp. 1-5. [Paper][Code]
Z. Yang et al., "Rogue Emitter Detection Using Hybrid Network of Denoising Autoencoder and Deep Metric Learning," ICC 2023 - IEEE International Conference on Communications, Rome, Italy, 2023, pp. 4780-4785.[Paper][Code]
Y. Ji et al., "Multi-Agent Reinforcement Learning Resources Allocation Method Using Dueling Double Deep Q-Network in Vehicular Networks," in IEEE Transactions on Vehicular Technology, vol. 72, no. 10, pp. 13447-13460, Oct. 2023.[Paper][Code]
X. Fu et al., "Semi-Supervised Specific Emitter Identification via Dual Consistency Regularization," in IEEE Internet of Things Journal, vol. 10, no. 21, pp. 19257-19269, Nov. 2023.[Paper][Code]
C. Wang et al., "Interpolative Metric Learning for Few-Shot Specific Emitter Identification," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2023.3296120.[Paper][Code]
Z. Yao et al., "Few-Shot Specific Emitter Identification Using Asymmetric Masked Auto-Encoder," in IEEE Communications Letters, vol. 27, no. 10, pp. 2657-2661, Oct. 2023.[Paper][Code]
H. Huang, G. Gui, H. Gacanin, C. Yuen, H. Sari and F. Adachi, "Deep Regularized Waveform Learning for Beam Prediction With Limited Samples in Non-Cooperative mmWave Systems," in IEEE Transactions on Vehicular Technology, vol. 72, no. 7, pp. 9614-9619, July 2023.[Paper][Code]
M. Tao et al., "Resource-Constrained Specific Emitter Identification Using End-to-End Sparse Feature Selection," GLOBECOM 2023 - 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia, 2023, pp. 6067-6072.[Paper][Code]
L. Xu et al., "Few-Shot Specific Emitter Identification Method Using Rotation Feature Decoupling for Secure 6G," 2023 IEEE 23rd International Conference on Communication Technology (ICCT), Wuxi, China, 2023, pp. 490-494.[Paper][Code]

2024

K. Xu et al., "Self-Supervised Learning Malware Traffic Classification Based On Masked Auto-Encoder," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3357072.[Paper][Code]
X. Zhang et al., "A-GCRNN: Attention Graph Convolution Recurrent Neural Network for Multi-Band Spectrum Prediction," in IEEE Transactions on Vehicular Technology, vol. 73, no. 2, pp. 2978-2982, Feb. 2024.[Paper][Code]
C. Liu et al., "Overcoming Data Limitations: A Few-Shot Specific Emitter Identification Method Using Self-Supervised Learning and Adversarial Augmentation," in IEEE Transactions on Information Forensics and Security, vol. 19, pp. 500-513, 2024.[Paper][Code]
Y. Peng et al., "Enhanced Specific Emitter Identification With Limited Data Through Dual Implicit Regularization," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3395441.[Paper][Code]
Y. Wang, H. Zhao, T. Ohtsuki, H. Sari and G. Gui, "Regularized Multi-Label Learning Empowered Joint Activity Recognition and Indoor Localization with CSI Fingerprints," in IEEE Transactions on Wireless Communications, doi: 10.1109/TWC.2024.3447786.[Paper][Code]
M. Tao et al., "Robust Specific Emitter Identification With Sample Selection and Regularization Under Label Noise," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3453297.[Paper][Code]
X. Fu, Y. Wang, Y. Lin, T. Ohtsuki, G. Gui and H. Sari, "Toward Robust Open-Set Radiofrequency Signal Identification in Internet of Things Using Hypersphere Manifold Embedding," in IEEE Internet of Things Journal, vol. 11, no. 24, pp. 41235-41247, 15 Dec.15.[Paper][Code]

2025

Y. Wang, T. Ohtsuki, Z. Sun, D. Niyato, X. Wang and G. Gui, "Avoiding Shortcuts: Enhancing Channel-Robust Specific Emitter Identification via Single-Source Domain Generalization," in IEEE Transactions on Wireless Communications, doi: 10.1109/TWC.2025.3528568.[Paper][Code]
Y. Wang and G. Gui, "Consistency-Guided Robust Learning for Content-Agnostic Radio Frequency Fingerprinting," in IEEE Communications Letters, doi: 10.1109/LCOMM.2025.3535879.[Paper][Code]