Current position: Home >>Research Focus
Shu Fu

Personal Information

Professor  
Supervisor of Doctorate Candidates  
Supervisor of Master's Candidates  

Research Focus

无人机辅助的网络智能应急服务理论

基于多维时效性的无人机智能应急服务机制;基于深度强化学习的无人机协同干扰管理;多无人机协同隐蔽通信;面向无人机协同的多智能体架构设计。

代表作

[1] “Joint Power Allocation and 3D Deployment for UAV-BSs: A game theory based deep reinforcement learning approach,” IEEE Transactions on Wireless Communications, vol. 23, no. 1, pp. 736-748, 2024.(一作)

[2] “Minimizing the average AoI of UAV aided covert communication with a DRL framework,” submitted to Chinese Journal of Aeronautics, pp. 1-12, 2024.(一作)

[3] “Caching placement optimization in UAV-assisted cellular networks: A deep reinforcement learning based framework,” IEEE Wireless Communications Letters, vol. 12, no. 8, pp. 1359-1363, 2023.(学生一作,导师通讯)

[4] “Towards energy-efficient data collection by unmanned aerial vehicle base station with NOMA for emergency communications in IoT,” IEEE Transactions on Vehicular Technology, vol. 72, no. 1, pp. 1211-1223, 2023.(一作)

[5] “Optimal hovering height and power allocation for UAV-aided NOMA covert communication system,” IEEE Wireless Communications Letters, vol. 12, no. 6, pp. 937-941, 2023.(学生一作,导师二作)

[6] “Towards energy-efficient UAV-assisted wireless networks using an artificial intelligence approach,” IEEE Wireless Communications, vol. 29, no. 5, pp. 77-83, 2022.(一作) 

[7] “An energy efficient intelligent framework of UAV enhanced vehicular networks,” IEEE Vehicular Technology Magazine, vol. 17, no. 2, pp. 94-102, 2022.(一作)

[8] “Energy-efficient UAV enabled data collection via wireless charging: a reinforcement learning approach,” IEEE Internet of Things Journal, vol. 8, no. 12, pp. 10209-10219, 2021.(一作)  

[9] “Joint 3D deployment and power allocation for UAV-BS: A deep reinforcement learning approach,” IEEE Wireless Communications Letters, vol. 10, no. 10, pp. 2309-2312, 2021.  (学生一作,导师通讯)

[10] 物联网数据收集中无人机路径智能规划,” 通信学报, 42(2): 124-133, 2021.(一作)

[11] “Joint unmanned aerial vehicle (UAV) deployment and power control for internet of things networks” IEEE Transactions on Vehicular Technology, vol. 69, no. 4, pp. 4367-4378, 2020.(一作)