Ni, Wei

Federated Multi-Agent Deep Reinforcement Learning for Resource Allocation of Vehicle-to-Vehicle Communications

Li, X., Lu, L., Ni, W., Jamalipour, A., Zhang, D., & Du, H. (2022) · IEEE Transactions on Vehicular Technology

Vehicular Ad Hoc Networks (VANETs)Traffic control and management

Cited by 188

Data and model poisoning backdoor attacks on wireless federated learning, and the defense mechanisms: A comprehensive survey

Wan, Y., Qu, Y., Ni, W., Xiang, Y., Gao, L., & Hossain, E. (2024) · IEEE Communications Surveys & Tutorials

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 152

Balancing Accuracy and Integrity for Reconfigurable Intelligent Surface-Aided Over-the-Air Federated Learning

Zheng, J., Tian, H., Ni, W., Ni, W., & Zhang, P. (2022) · IEEE Transactions on Wireless Communications

Advanced Wireless Communication TechnologiesPrivacy-Preserving Technologies in Data

Cited by 47

Data-Agnostic Model Poisoning Against Federated Learning: A Graph Autoencoder Approach

Li, K., Zheng, J., Yuan, X., Ni, W., Akan, O. B., & Poor, H. V. (2024) · IEEE Transactions on Information Forensics and Security

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 41

Joint User, Channel, Modulation-Coding Selection, and RIS Configuration for Jamming Resistance in Multiuser OFDMA Systems

Yuan, X., Hu, S., Ni, W., Liu, R. P., & Wang, X. (2023) · IEEE Transactions on Communications

Advanced Wireless Communication TechnologiesAdvanced Antenna and Metasurface Technologies

Cited by 33

Dispersed Pixel Perturbation-Based Imperceptible Backdoor Trigger for Image Classifier Models

Wang, Y., Zhao, M., Li, S., Yuan, X., & Ni, W. (2022) · IEEE Transactions on Information Forensics and Security

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 26

Optimal Adaptive Power Control for Over-The-Air Federated Edge Learning Under Fading Channels

Yu, X., Xiao, B., Ni, W., & Wang, X. (2023) · IEEE Transactions on Communications

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 19

Privacy-Preserving Multi-Agent Deep Reinforcement Learning for Effective Resource Auction in Multi-Access Edge Computing

You, F., Yuan, X., Ni, W., & Jamalipour, A. (2025) · IEEE Transactions on Cognitive Communications and Networking

IoT and Edge/Fog ComputingPrivacy-Preserving Technologies in Data

Cited by 15

A Novel Privacy-Preserving Incentive Mechanism for Multi-Access Edge Computing

You, F., Yuan, X., Ni, W., & Jamalipour, A. (2024) · IEEE Transactions on Cognitive Communications and Networking

IoT and Edge/Fog ComputingPrivacy-Preserving Technologies in Data

Cited by 11

Employing Intelligent Aerial Data Aggregators for the Internet of Things: Challenges and Solutions

Li, K., Ni, W., Noor, A., & Guizani, M. (2022) · IEEE Internet of Things Magazine

UAV Applications and OptimizationIoT Networks and Protocols

Cited by 11

Optimal Power Control for Over-The-Air Federated Edge Learning Using Statistical Channel Knowledge

Yu, X., Xiao, B., Ni, W., & Wang, X. (2022) · 2022 14th International Conference on Wireless Communications and Signal Processing (WCSP)

Privacy-Preserving Technologies in DataIoT and Edge/Fog Computing

Cited by 4