入选北航青年拔尖人才支持计划，主持国家自然科学基金青年项目1项，以第一作者或通信作者身份发表 SCI-Q1区期刊论文12篇（其中2篇入选 ESI全球前1%高被引论文，1篇入选 ESI研究前沿核心论文），在IEEE Globecom/ICC等国际会议发表论文10篇，谷歌学术引用1200余次，单篇最高SCI他引300余次，获2022年中国电子学会自然科学一等奖（排名4）。

在6G无线通信网络前沿应用领域从事应用基础研究和关键技术研发，研究方向包括移动人工智能，无线联邦学习，空天地一体化网络，欢迎对以上研究方向感兴趣的学生保送或报考硕士、博士研究生，联系方式：dliu@buaa.edu.cn

专著章节：

1. Dong Liu and Chenyang Yang, “Caching with Recommendation and Reinforcement Learning” in Edge Caching for Mobile Networks, Edited by H. Vincent Poor and Wei Chen, IET, 2021.

期刊论文：

1. Binqiang Chen, Dong Liu*, Jianlong Zhang, and Lajos Hanzo, “Learning-Aided UAV-Cooperation Reduces the Age-of-Information in Wireless Networks,” IEEE Communications Letter, early access, 2024.

2. Siyang Tan, Binqiang Chen, Dong Liu*, Jianlong Zhang, and Lajos Hanzo, “Communication-assisted multi-Agent Reinforcement Learning Improves Task-Offloading in UAV-Aided Edge-Computing Networks,” IEEE Wireless Communications Letter, vol 12, no. 12, Dec. 2023.

3. Dong Liu, Jiankang Zhang, Jingjing Cui, Robert Maunder, Soon-Xin Ng, and Lajos Hanzo, “Deep Learning Aided Routing for Space-Air-Ground Integrated Networks Relying on Real Satellite, Flight, and Shipping Data,” IEEE Wireless Communications, vol. 29, no. 2, Apr. 2022.

4. Dong Liu, Jiankang Zhang, Jingjing Cui, Robert Maunder, Soon-Xin Ng, and Lajos Hanzo, “Deep Learning Aided Packet Routing in Aeronautical Ad-Hoc Networks Relying on Real Flight Data: From Single-Objective to Near-Pareto Multi-Objective Optimization,” IEEE Internet of Things Journal, vol. 9, no. 6, pp. 4598-4614, Mar. 2022.

5. Dong Liu, Jingjing Cui, Jiankang Zhang, Chenyang Yang, and Lajos Hanzo, “Deep Reinforcement Learning Aided Packet-Routing For Aeronautical Ad-Hoc Networks Formed by Passenger Planes,” IEEE Transactions on Vehicular Technology, vol. 70, no. 5, pp 5166-5171, May 2021.

6. Dong Liu, Jianyu Zhao, Chenyang Yang, and Lajos Hanzo, “Accelerating Deep Reinforcement Learning with the Aid of Partial Model: Energy-Efficient Predictive Video Streaming,” IEEE Transactions on Wireless Communications, vol. 20 no. 6, Jun. 2021.

7. Dong Liu, Chengjian Sun, Chenyang Yang, and Lajos Hanzo, “Optimizing Wireless Systems Using Unsupervised and Reinforced-Unsupervised Deep Learning,” vol. 34, no. 4, pp. 270-277, IEEE Network, Jul./Aug. 2020.

8. Dong Liu and Chenyang Yang, “Caching at Base Stations with Heterogeneous User Demands and Spatial Locality,” IEEE Transactions on Communications, vol. 67, no. 2, pp 1554-1569, Feb. 2019.

9. Dong Liu and Chenyang Yang, “Caching Policy Toward Maximal Success Probability and Area Spectral Efficiency of Cache-enabled HetNets,” IEEE Transactions on Communications, vol. 65, no.6, pp.2699-2714, Jun. 2017.

10. Dong Liu, Binqiang Chen, Chenyang Yang, and Andreas F. Molisch, “Caching at the Wireless Edge: Design Aspects, Challenges and Future Directions,” IEEE Communications Magazine, vol. 54, no. 9, pp. 22-28, Sept. 2016. (ESI高被引论文, ESI研究前沿核心论文)

11. Dong Liu and Chenyang Yang, “Energy Efficiency of Downlink Networks with Caching at Base Stations,” IEEE Journal on Selected Areas in Communications, vol. 34, no. 4, pp. 907-922, Apr. 2016. (ESI高被引论文)

12. Dong Liu, Shengqian Han, Chenyang Yang, and Qian Zhang, “Semi-Dynamic User-Specific Clustering for Downlink Cloud Radio Access Network,” IEEE Transactions on Vehicular Technology, vol. 65, no. 4, pp. 2063-2077, Apr. 2016.

13. Tiep M Hoang, Dong Liu, Thien Van Luong, Jiankang Zhang, and Lajos Hanzo, “Deep Learning Aided Physical-Layer Security: The Security versus Reliability Trade-off,” IEEE Transactions on Cognitive Communications and Networking, vol. 8, no. 2, June 2022.

14.  Tiep Hoang, Thien Van Luong, Dong Liu, and Lajos Hanzo, “RIS-aided AANETs: Security Maximization Relying on Unsupervised Projection-based Neural Networks,” IEEE Transactions on Vehicular Technology, vol. 71, no. 2, Feb. 2022.

15. Jiankang Zhang, Luping Xiang, Dong Liu, Cui Jingjing, Soon Xi Ng, Robert Maunder, Thomas Graupl, Uwe Fiebig, and Lajos Hanzo, “Semi-Stochastic Aircraft Mobility Modelling for Aeronautical Networks: An Australian Case-Study Based on Real Flight Data,” IEEE Transactions on Vehicular Technology, vol. 70, no. 10, Oct. 2021.

16. Jingjing Cui, Soon Xin Ng, Dong Liu, Jiankang Zhang, Arumugam Nallanathan, and Lajos Hanzo, “Multi-Objective Optimization for Integrated Ground-Air-Space Networks,” IEEE Vehicular Technology Magazine, vol. 16, no. 3, pp. 88-98, Sept. 2021.

会议论文：

1. Dong Liu, Jianyu Zhao, and Chenyang Yang, “Energy-Saving Predictive Video Streaming with Deep Reinforcement Learning,” IEEE Globecom, 2019.

2. Dong Liu and Chenyang Yang, “A Learning-based Approach to Joint Content Caching and Recommendation at Base Stations,” IEEE Globecom, 2018.

3. Dong Liu and Chenyang Yang, “When Exploiting Individual User Preference Is Beneficial for Caching at Base Stations”, IEEE ICC Workshop, 2018.

4. Dong Liu and Chenyang Yang, “Optimal Content Placement for Offloading in Cache-enabled Heterogeneous Wireless Networks,” IEEE Globecom, 2016.

5. Dong Liu and Chenyang Yang, “Cache-enabled Heterogeneous Cellular Networks: Comparison and Tradeoffs,” IEEE ICC, 2016.

6. Dong Liu and Chenyang Yang, “Will Caching at Base Station Improve Energy Efficiency of Downlink Transmission,” IEEE GlobalSIP, 2014.

7. Dong Liu, Qian Zhang, Shengqian Han, Chenyang Yang, Gang Wang, and Ming Lei, “Semi-dynamic Cooperative Cluster Selection for Downlink Coordinated Beamforming Systems,” IEEE WCNC, 2014.

8. Binqiang Chen, Dong Liu, and Lajos Hanzo, “Decentralized Trajectory and Power Control Based on Multi-Agent Deep Reinforcement Learning in UAV Networks,” IEEE ICC, 2022.

9. Pengyu Cong, Chenjiang Sun, Dong Liu, and Chenyang Yang, “Optimizing Caching Policy and Bandwidth Allocation Towards User Fairness,” IEEE WCNC, 2020.

10. Chengjian Sun, Dong Liu, and Chenyang Yang, “Model-Free Unsupervised Learning for Optimization Problems with Constraints,” IEEE APCC, 2019. 

• [1]. 2013.9 -- 2019.1

  北京航空航天大学       信息与通信工程       博士研究生毕业       工学博士学位

• [2]. 2009.9 -- 2013.7

  北京航空航天大学       信息与通信工程       大学本科毕业       工学学士学位

• [1].

  英国南安普顿大学      博士后

• [1] 无线联邦学习
• [2] 空天地一体化网络
• [3] 移动人工智能
• [4] 边缘计算与缓存