学术论文
代表性成果如下：
- D. Wang, D. Chen, B. Song, N. Guizani, X. Yu, and X. Du, “From IoT to 5G I-IoT: The Next Generation IoT-Based Intelligent Algorithms and 5G Technologies,” IEEE Communications Magazine, vol. 56, no. 10, pp. 114-120, 2018.
- D. Wang, B. Song, D. Chen, and X. Du, “Intelligent Cognitive Radio in 5G: AI-Based Hierarchical Cognitive Cellular Networks,” IEEE Wireless Communications, vol. 26, no. 3, pp. 54-61, 2019.
- D. Wang, B. Song, N. Zhao, P. Lin, and F. R. Yu, “Resource Management for Secure Computation Offloading in Softwarized Cyber-Physical Systems,” IEEE Internet of Things Journal, vol. 8, no. 11, pp. 9294-9304, 2021.
- D. Wang, W. Zhang, B. Song, X. Du, and M. Guizani, “Market-Based Model in CR-IoT: A Q-Probabilistic Multi-Agent Reinforcement Learning Approach,” IEEE Transactions on Cognitive Communications and Networking, 2021.
- D. Wang, B. Song, P. Lin, F. R. Yu, X. Du, and M. Guizani, “Resource Management for Edge Intelligence (EI)-Assisted IoV Using Quantum-Inspired Reinforcement Learning,” IEEE Internet of Things Journal, doi: 10.1109/JIOT.2021.3137984, 2022.
- D. Wang, B. Li, B. Song Y. Liu, K. Muhammand, and X. Zhou, “Dual-Driven Resource Management for Sustainable Computing in the Blockchain-Supported Digital Twin IoT”, IEEE Internet of Things Journal, doi:10.1109/JIOT.2022.3162714, 2022.
- D. Wang, B. Song, Y. Liu, M. Wang, “Secure and Reliable Computation Offloading in Blockchain-assisted Cyber-Physical IoT Systems,” Digital Communications and Networks, doi: 10.1016/j.dcan.2022.05.025, 2022.
- D. Wang, Y. Bai, G. Huang, B. Song and F. R. Yu, “Cache-Aided MEC for IoT: Resource Allocation Using Deep Graph Reinforcement Learning,” IEEE Internet of Things Journal, doi: 10.1109/JIOT.2023.3244909, 2023.
- D. Wang, Yingjie Liu and Bin Song, “A Credible Trafffc Prediction Method Based on Self-supervised Causal Discovery”, Science China Information Sciences, Accept, 2023.
- D. Wang, Bo Li, Bin Song, Chen Chen and Fei Richard Yu, “HSMH: A Hierarchical Sequence Multi-hop Reasoning Model with Reinforcement Learning,” IEEE Transactions on Knowledge and Data Engineering, 2023.08, Accept. 10.1109/TKDE.2023.3303617.
论文详情见Google Scholar