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Education
- Ph.D., University of Waterloo, Ontario, Canada, 2016
- B. Eng., Tsinghua University, Beijing, China, 2010
Research
- Wireless Communications and Networking
- Unmanned Aerial Vehicle (UAV) Communication Networks
- Artificial Intelligence and Machine Learning
- 5G and Beyond 5G Communications
- Radio Resource Management
Selected Publications
- L. Wang, S. Tripathi, R. Zhang, N. Cheng, and M. Wang, “Optimal Charging Profile Design for Solar-Powered Sustainable UAV Communication Networks,” IEEE ICC 2023, Rome, Italy, May 28 – June 21, 2023
- R. Zhang, D. M. Nguyen, Miao Wang, Lin X. Cai and X. Shen,”Responsive Regulation of Dynamic UAV Communication Networks Based on Deep Reinforcement Learning,” Broadband Communications, Computing and Control for Ubiquitous Intelligence, Wireless Network Book Series, Springer, pp. 35-63, 2022
- L. Liu, B. Lin, R. Zhang, Y. Che, and C. Zhang, “Joint Beamforming and Deployment Optimization for UAV-Assisted Maritime Monitoring Networks”, International Conference on Wireless Algorithms, Systems, and Applications (WASA), 2022 (Best Paper Award).
- Z. Chen, R. Zhang, L. X. Cai, Y. Chen, and Y. Liu, “A Deep Reinforcement Learning based Approach for NOMA-based Random Access Network with Truncated Channel Inversion Power Control“, IEEE ICC 2022, Seoul, Korea, May 16-20, 2022
- R. Zhang, M. Wang, L. X. Cai, and X. Shen, “Learning to be Proactive: Self-Regulation of UAV Based Networks with UAV and User Dynamics“, IEEE Transactions on Wireless Communications,vol. 20, no. 7, pp. 4406-4419, 2021
- Z, Chen, R. Zhang, Y. Liu, L. X. Cai, and Q. Chen, “Performance Study of Cybertwin-assisted Random Access NOMA,” IEEE Internet of Things Journal, vol. 8, no. 22, pp. 16279-16289, 2021
- R. Zhang, M. Wang, and L. X. Cai, “SREC: Proactive Self-REmedy of Energy-Constrained UAV-Based Networks via Deep Reinforcement Learning,” IEEE GlobeCom2020, Taipei, Taiwan, Dec. 7-11, 2020
