Wen Wu
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Selected Publications (# marks the corresponding author)

Note that the full list can be found in [here]. IEEE Copyright: Personal use of the materials is permitted, but republication/redistribution requires IEEE permission.

Books

  1. W. Wu, S. Zhang, P. Dong, and X. Shen (authors), “Collaborative Edge AI over 6G Networks,” Springer Verlag, proposal approved, 2026.

  2. P. Yang, W. Wu, N. Zhang, and X. Shen (authors), “Millimeter-Wave Networks: Beamforming Design and Performance Analysis,” Springer Verlag, 2021. (ISBN-10: 3030886298, ISBN-13: 9783030886295) [pdf]

  3. W. Wu, Y. Tang, P. Yang, W. Zhang, and N. Zhang, “Collaborative Deep Neural Network Inference via Mobile Edge Computing,” Broadband Communications, Computing, and Control for Ubiquitous Intelligence, pp. 263-190. Editors: L. Cai, B. L. Mark, and J. Pan, Springer, 2022. [pdf]

Journal

  1. [arXiv] M. Guo, W. Wu#, Y. Wang, and S. Zhang, “Large-Small Model Collaboration for LEO Satellite Networks: An Agentic AI Approach,” IEEE Transactions on Cognitive Communications and Networking, submission.

  2. [arXiv] J. Cong, W. Wu#, C. You, J. Huang, and K. Shang, “Transformer-Enhanced DRL for Resource Management in Low-Altitude Surveillance Network,” IEEE Transactions on Cybernetics, submission.

  3. [arXiv] Y. Wang, W. Wu#, K. Qu, and X. Shen, “Edge-Accelerated Cooperative Sensing over CAV Networks: A Transformer-Based RL Approach,” IEEE Transactions on Mobile Computing, submission.

  4. [arXiv] S. Zhang, W. Wu#, L. Li, Y. Wang, and X. Shen, “Communication-Efficient Collaborative LLM Inference over LEO Satellite Networks,” IEEE Journal on Selected Areas in Communications, submission, 2025.

  5. [arXiv] Z. Li, W. Wu#, S. Wu, and X. Shen, “Fast AI Model Partition for Split Learning over Edge Networks,” IEEE Transactions on Mobile Computing, under revision, 2025.

  6. [arXiv] Z. Mao, W. Wu#, and X. Shen, “Learning-Based Radio Resource Management and Bitrate Adaptation for Multi-UAV Video Streaming over Low-Altitude Wireless Networks,” IEEE Journal of Selected Topics in Signal Processing, under revision, 2025.

  7. [arXiv] K. Shang, W. Wu#, J. Tang, Z. Mao, and X. Shen, “Energy-Efficient RAN Slicing via Parameterized Deep Reinforcement Learning,” IEEE Transactions on Cognitive Communications and Networking, major revision, 2025.

  8. [arXiv] J. Cong, W. Wu#, C. You, J. Huang, and Z. Mao, “Data Generation for Heterogeneous Federated Learning in Wireless Networks via Diffusion Model,” IEEE Transactions on Network Science and Engineering, revision, 2026.

  9. [arXiv] B. Liu, Q. Zhang, Y. Lu, J. Jiao, C. Jagmohan, W. Wu, J. Zhang, and K. Dimitrios, “MobileROS: A Wireless-Native Robot Operating System for Mobile Robotics,” IEEE Transactions on Robotics, conditionaly accepted.

  10. [TWC] W. Jiang, B. Ai, W. Wu#, L. Qian, and L. Liu, “Energy-Efficient Aerial IRS Configuration and Resource Allocation in AoI-Aware MEC,” IEEE Transactions on Wireless Communications, to appear. [pdf] （中科院1区Top）

  11. [TMC] H. Tu, W. Wu#, L. Chen, L. Li, X. Chen, and X. Shen, “FL in Motion: Accelerating FL via Mobility-Aware Vehicle Selection and Sparse Training,” IEEE Transactions on Mobile Computing, to appear. [pdf]（CCF A，中科院1区Top）

  12. [Network] W. Wu, X. Huang, M. Qin, Q. Li, N. Cheng, and T. H. Luan, “AI-Native Network Digital Twin for Intelligent Network Management in 6G,” IEEE Network, to appear. [pdf] （中科院2区）

  13. [COMNET’26] H. Tu, W. Wu#, L. Li, Y. Lu, L. Chen, and X. Chen, “V-FedMM: Dynamic Sample Selection for Efficient Multimodal Federated Learning over Vehicular Networks,” Computer Networks (Elsevier), to appear. [pdf] （CCF B）

  14. [TCCN’26] L. Li, W. Wu#, S. Fang, S. Wang, and C. Yin, “Wider Eyes in the Sky: Scene-Adaptive Video Analytics in Low-Altitude Surveillance Networks,” IEEE Transactions on Cognitive Communications and Networking, vol. 12, pp. 4624 - 4639, 2026. [pdf] （中科院1区Top）

  15. [TNSE’26] X. Cheng, W. Wu#, Y. Wang, Z. Mao, Y. Lu, and P. Dong, “Dependency-Aware CAV Task Scheduling via Diffusion-Based Reinforcement Learning,” IEEE Transactions on Network Science and Engineering, vol. 13, pp. 4797 - 4814, 2026. [pdf] （中科院2区）

  16. [IoTJ’25] X. Chen, W. Wu#, F. Ji, Y. Lu, and L. Li, “Privacy-Aware SFL for Resource-Efficient LLM Fine-Tuning over IoT Devices,” IEEE Internet of Things Journal, vol. 12, no. 24, pp. 51902 - 51913, Dec. 2025. [pdf] （中科院2区Top）

  17. [JSTSP’25] L. Li, X. Yang, W. Wu#, H. Wang, T. Ohtsuki, M. Pan, and X. Shen, “MobiLLM: Enabling On-Device Fine-Tuning of Billion-Sized LLMs via Server-Assisted Side-Tuning,” IEEE Journal of Selected Topics in Signal Processing, vol. 19, no. 7 pp. 1251 - 1265, 2025. [pdf]（中科院1区Top）

  18. [JSTSP’25] S. Zhang, G. Cheng, W. Wu#, X. Huang, L. Song, and X. Shen, “Split Fine-Tuning for Large Language Models in Wireless Networks,” IEEE Journal of Selected Topics in Signal Processing, vol. 19, no. 7, pp. 1376 - 1391, Oct. 2025. [pdf]（中科院1区Top）

  19. [SCIS’25] W. Wu, and X. Huang, “Split-LEO: Efficient AI Model Training over LEO Satellite Networks,” SCIENCE CHINA Information Sciences, vo. 68, no. 190305, 2025. [pdf]（CCF A, 中科院1区Top）

  20. [IoTM’25] X. Chen, W. Wu#, L. Li and F. Ji, “LLM-Empowered IoT for 6G Networks: Architecture, Challenges, and Solutions,” IEEE Internet of Things Magazine, vol. 8, no. 6, pp. 34-41, Nov. 2025. [pdf]

  21. [TMC’25] S. Zhang, W. Wu#, L. Song, and X. Shen, “Efficient Model Training in Edge Networks with Hierarchical Split Learning,” IEEE Transactions on Mobile Computing, vol. 24, no. 10, pp. 10214 - 10229, Oct. 2025. [pdf] （CCF A, 中科院1区Top）

  22. [IoTM’25] Z. Li, S. Wu, W. Wu#, Q. Lin, Y. Sun, and H. Wang, “Split Knowledge Distillation for Large Models in IoT: Architecture, Challenges, and Solutions,” IEEE Internet of Things Magazine, vol. 8, no. 5, pp. 16 - 23, Sep. 2025. [pdf]

  23. [TWC’24] K. Qu, W. Zhuang, Q. Ye, W. Wu#, and X. Shen, “Model-Assisted Learning for Adaptive Cooperative Perception of Connected Autonomous Vehicles,” IEEE Transactions on Wireless Communications, vol. 23, no. 8, pp. 8820-8835, Aug. 2024. [pdf] （中科院1区Top）

  24. [JSTSP’24] X. Huang, W. Wu, S. Hu, M. Li, C. Zhou, and X. Shen, “Digital Twin Based User-Centric Resource Management for Multicast Short Video Streaming”, IEEE Journal of Selected Topics in Signal Processing, vol. 18, no. 1, pp. 50-65, Jan. 2024. [pdf] （中科院1区）

  25. [JSAC’23] W. Wu, M. Li, K. Qu, C. Zhou, X. Shen, W. Zhuang, X. Li, and W. Shi, ”Split Learning over Wireless Networks: Parallel Design and Resource Management,” IEEE Journal on Selected Areas in Communications, vol. 41, no. 4, pp. 1051-1066, Apr. 2023. [pdf] （CCF A, 中科院1区Top, ESI Highly Cited Paper）

  26. [IoTJ’23] K. Qu, W. Zhuang, W. Wu#, M. Li, X. Shen, X. Li, and W. Shi, “Stochastic Cumulative DNN Inference with RL-Aided Adaptive IoT Device-Edge Collaboration,” IEEE Internet of Things Journal, vol. 10, no. 20, pp. 18000 - 18015, Oct. 2023. [pdf] （中科院1区）

  27. [WCM’22] W. Wu, C. Zhou, M. Li, H. Wu, H. Zhou, N. Zhang, X. Shen, and W. Zhuang, “AI-Native Network Slicing for 6G Networks,” IEEE Wireless Communications, vol. 29, no. 1, pp. 96–103, Feb. 2022. [pdf] （中科院1区, ESI Highly Cited Paper）

  28. [COMST’22] X. Shen, J. Gao, W. Wu, M. Li, C. Zhou, and W. Zhuang, “Holistic Network Virtualization and Pervasive Network Intelligence for 6G,” IEEE Communications Surveys and Tutorials, vol. 24, no. 1, pp. 1-30, 1st. Quart. 2022. [pdf] （中科院1区Top, Editor-in-Chief Invited Paper, Cover Paper, ESI Highly Cited Paper）

  29. [TII’21] W. Wu, P. Yang, W. Zhang, C. Zhou, and X. Shen, “Accuracy-Guaranteed Collaborative DNN Inference in Industrial IoT via Deep Reinforcement Learning,” IEEE Transactions on Industrial Informatics, vol. 17, no. 7, pp. 4988–4998, July 2021. [pdf] （中科院1区）

  30. [JSAC’21] W. Wu, N. Chen, C. Zhou, M. Li, X. Shen, W. Zhuang, and X. Li, “Dynamic RAN Slicing for Service-Oriented Vehicular Networks via Constrained Learning,” IEEE Journal on Selected Areas in Communications, vol. 39 no. 7, pp. 2076–2089, July 2021. [pdf]（CCF A, 中科院1区Top）

  31. [TWC’21] C. Zhou, W. Wu, H. He, P. Yang, F. Lyu, N. Cheng, and X. Shen, “Deep Reinforcement Learning for Delay-Oriented IoT Task Scheduling in Space-Air-Ground Integrated Network,” IEEE Transactions on Wireless Communications, vol. 20, no. 2, pp. 911-925, Feb. 2021. [pdf] （中科院1区Top, ESI Highly Cited Paper）

  32. [OJVT’20] X. Shen, J. Gao, W. Wu, K. Lyu, M. Li, W. Zhuang, X. Li, and J. Rao, “AI-assisted Network-slicing based Next-generation Wireless Networks,” IEEE Open Journal of Vehicular Technology, vol. 1, no. 1, pp. 45-66, Jan. 2020. [pdf] （中科院2区, Editor-in-Chief Invited Paper, IEEE Vehicular Technology Society OJVT Best Paper Award）

  33. [TVT’20] W. Wu, N. Cheng, N. Zhang, P. Yang, K. Aldubaikhy, and X. Shen, “Performance Analysis and Enhancement of Beamforming Training in 802.11ad,” IEEE Transactions on Vehicular Technology, vol. 69, no. 5, pp. 5293-5306, May 2020. [pdf] （中科院2区）

  34. [TWC’19] W. Wu, N. Cheng, N. Zhang, P. Yang, W. Zhuang, and X. Shen, “Fast mmwave Beam Alignment via Correlated Bandit Learning,” IEEE Transactions on Wireless Communications, vol. 18, no. 12, pp. 5894-5908, Dec. 2019. [pdf] （中科院1区Top）

  35. [TVT’19] W. Wu, N. Zhang, N. Cheng, Y. Tang, K. Aldubaikhy, and X. Shen, “Beef up mmWave Dense Cellular Networks with D2D-Assisted Cooperative Edge Caching,” IEEE Transactions on Vehicular Technology, vol. 68, no. 4, pp. 3890-3904, Apr. 2019. [pdf] （中科院2区）

Conference

  1. [ICCT’25] K. Shang, W. Wu#, J. Tang, J. Cong, Z. Mao, and X. Shen, “Adaptive RAN Slicing for Diffusion-based AIGC Services in Mobile Edge Networks,” in Proc. IEEE ICCT, Shenyang, China, Oct. 16-18, 2025. (Best Student Paper Award )

  2. [Mobicom Workshop’25] L. Li, and W. Wu#, “Memory-Efficient LLM Fine-Tuning on the Mobile Device via Server Assisted Side Tuning,” in Proc. ACM Mobicom Workshop, Hong Kong, Nov. 4-8, 2025. [pdf] (Mobicom Workshop Best Paper Award )

  3. [ICDCS’24] Y. Lu and W. Wu#, “Digital Twin Assisted Cross-Layer Resource Scheduling in ORAN System,” in Proc. IEEE ICDCS PhD Student Symposium, New Jersey, USA, July 23-26, 2024. [pdf] （CCF B）

  4. [USENIX Security’24] S. Li, X. Wang, M. Xue, H. Zhu, Z. Zhang, Y. Gao, W. Wu, and X. Shen, “Yes, One-Bit-Flip Matters! Universal DNN Model Inference Depletion with Runtime Code Fault Injection,” in Proc. USENIX Security (Security), Philadelphia, USA, August 14–16, 2024. [pdf] （CCF A, Distinguished Paper Award ）

  5. [ICDCS’23] X. Huang, W. Wu#, and X. Shen, “Digital Twin-Assisted Resource Demand Prediction for Multicast Short Video Streaming,” in Proc. IEEE International Conference on Distributed Computing Systems (ICDCS) PhD Student Symposium, Hong Kong, China, July 18-21, 2023. [pdf] （CCF B）

  6. [ICDCS’23] S. Zhang, W. Wu#, P. Hu, S. Li, and N. Zhang, “Split Federated Learning: Speed up Model Training in Resource-Limited Wireless Networks,” in Proc. IEEE International Conference on Distributed Computing Systems (ICDCS) PhD Student Symposium, Hong Kong, China, July 18-21, 2023. [pdf] （CCF B）

  7. [ICCC’22] W. Wu, K. Qu, P. Yang, N. Zhang, X. Shen, and W. Zhuang, “Cost-Effective Two-Stage Network Slicing for Edge-Cloud Orchestrated Vehicular Networks,” in Proc. IEEE/CIC International Conference on Communications in China (ICCC), Foshan, China, 2022. [pdf] (Best Paper Award )

Patents

  1. [US Patent] X. Shen, W. Wu, M. Li, K. Qu, C. Zhou, W. Zhuang, and X. Li, “Systems and Methods for Cluster-Based Parallel Split Learning”. United States, App. 18,884,763, 2024/09/13. Patent Status: Granted/Issued. Year Issued: 2025/01/02. [pdf]