1. Filtered randomized smoothing: A new defense for robust modulation classification
Wenhan Zhang, Meiyu Zhong, Ravi Tandon, and Marwan Krunz Proc. of the IEEE Military Communications Conference (MILCOM) 2024 – Track 5, Washington, DC, Oct. 28 – Nov. 1, 2024.
2. Stealthy adversarial attacks on machine learning-based classifiers of wireless signals
Wenhan Zhang, Marwan Krunz, and Gregory Ditzler IEEE Transactions on Machine Learning in Communications and Networking (TMLCN), vol. 2, pp. 261-279, Feb. 2024, doi: 10.1109/TMLCN.2024.3366161.
3. CyPA: A cyclic prefix assisted DNN for protocol classification in shared spectrum
Wenhan Zhang, Marwan Krunz, and Md Rabiul Hossein Proc. of the IEEE International Conference on Computing, Networking and Communications (ICNC) 2024: AI and Machine Learning for Communications and Networking, Feb. 2024 (acceptance rate 24.10%).
4. DL-SIC: Deep learning aided successive interference cancellation in shared spectrum
Zhiwu Guo, Wenhan Zhang, Ming Li, Marwan Krunz, and Mohammad Hossein Manshaei Proc. of the IEEE International Conference on Computing, Networking and Communications (ICNC) 2024: AI and Machine Learning for Communications and Networking, Feb. 2024.
6. Dynamic spectrum access in non-stationary environments: A DRL-LSTM integrated approach
Mingjie Feng, Wenhan Zhang, and Marwan Krunz Proc. of the IEEE International Conference on Computing, Networking and Communications (ICNC) 2023: AI and Machine Learning for Communications and Networking, Feb. 2023.
7. Machine learning based protocol classification in unlicensed 5 GHz bands
Wenhan Zhang and Marwan Krunz Proc. of the IEEE International Conference on Communications (ICC) 2022 Conference - Workshop on Spectrum Sharing Technology for Next Generation Communications, Seoul, South Korea, May 2022.
8. Application of adversarial machine learning in protocol and modulation misclassification
Marwan Krunz, Wenhan Zhang, and Gregory Ditzler Proc. of the Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications Conference (part of SPIE Defense and Commercial Sensing Symposium), April 2022.
9. Joint task partitioning and user association for latency minimization in mobile edge computing networks
Mingjie Feng, Marwan Krunz, and Wenhan Zhang IEEE Transactions on Vehicular Technology (TVT), vol. 70, no. 8, pp. 8108-8121, Aug. 2021.
10. Intelligent jamming of deep neural network based signal classification for shared spectrum
Wenhan Zhang, Marwan Krunz, and Gregory Ditzler Proc. of the IEEE Military Communications Conference (MILCOM) 2021 – Track 5, San Diego, Nov. 29 – Dec. 2, 2021.
11. Task partitioning and user association for latency minimization in mobile edge computing networks
Mingjie Feng, Marwan Krunz, and Wenhan Zhang Proc. of the IEEE International Workshop on Intelligent Cloud Computing and Networking (ICCN) 2021 in conjunction with the IEEE INFOCOM 2021 Conference, May 2021.
12. Signal detection and classification in shared spectrum: A deep learning approach
Wenhan Zhang, Mingjie Feng, and Marwan Krunz Proc. of the IEEE International Conference on Computer Communications (INFOCOM) 2021 Conference, May 2021 (acceptance rate 19.9%).
13. Latency prediction for delay-sensitive V2X applications in mobile cloud/edge computing systems
Wenhan Zhang, Mingjie Feng, Marwan Krunz, and Haris Volos Proc. of the IEEE Global Communications Conference (GLOBECOM) Conference, Taipei, Taiwan, Dec. 2020.
