Wen Wu
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Full List of Publications (# marks the corresponding authors)

IEEE Copyright: Personal use of the materials is permitted, but republication/redistribution requires IEEE permission.

Books/Book Chapters

  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. S. Li, H. Zhu, W. Wu, and X. Shen (authors), “Backdoor Attacks against Deep Learning Based Sensing Algorithms,” Springer Verlag, 2024 (ISBN-10: 3031573889, ISBN-13: 978-3031573880). [pdf]

  4. L. Fu, S. Liu, W. Wu, N. Zhang, and W. Zhuang (authors), MAC Protocol Design for Full-duplex Enabled Wireless Networks, Springer Verlag, 2024. (ISBN 978-3031572951) [pdf]

  5. 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]

  6. Q. Ye and W. Wu, “Network Slicing for 5G Networks and Beyond,” Broadband Communications, Computing, and Control for Ubiquitous Intelligence, pp. 17-34. Editors: L. Cai, B. L. Mark, and J. Pan, Springer, 2022. [pdf]

  7. Y. Tang and W. Wu, “Routing Algorithms for Heterogeneous Vehicular Networks,” Broadband Communications, Computing, and Control for Ubiquitous Intelligence, pp. 17-34. Editors: L. Cai, B. L. Mark, and J. Pan, Springer, 2022. [pdf]

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Preprints

Journal

  1. [JSAC] 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.

  2. [JSTSP] 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, submission, 2025.

  3. [TMC] Z. Li, W. Wu#, S. Wu, and X. Shen, ‘‘Fast AI Model Partition for Split Learning over Edge Networks,” IEEE Transactions on Mobile Computing, submission, 2025.

  4. [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, major revision, 2025.

  5. [TMC] R. Chen, C. Yi, H. Zhu, H. Du, W. Wu, J. Kang, and D. Niyato, ‘‘Dynamic Digital Twin Update by Adaptive Model Splitting and Reliable Crowdsourcing under Uncertain Data Distortions,” IEEE Transactions on Mobile Computing, submission, 2025.

  6. [TRO] 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, under revision, 2025.

  7. [TPAMI] M. Du, H. Tang, W. Wu#, H. Chen, W. Zhang, P. Jiao, and H. Wu, ‘‘HyperRole: Hyperbolic Graph Transformer with Multi-Scale Feature Fusion for Role Discovery",” IEEE Transactions on Pattern Analysis and Machine Intelligence, submission, 2025.

  8. [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, under revision, 2025.

  9. [TWC] Z. Meng, X. Zhuo, Y. Hu, W. Wu, L. Tang, F. Qu, C. Xu, and Y. Zhao, ‘‘Joint LEO Satellite Scheduling and Beamforming Design for Non-Cooperative Maritime Target Location Sensing,” IEEE Transactions on Wireless Communications, submission, 2025.

  10. [TCCN] 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.

  11. [TNSE] 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, 2025.

  12. [TVT] H. Jia, Y. Wang, and W. Wu#, ‘‘Demand-Aware User Association and Beamforming Design in Integrated Satellite-Terrestrial Networks,” IEEE Transactions on Vehicular Technology, under revision, 2024.

  13. [IOTJ] Y. Deng, S. Wu, J. You, W. Wu, Y. Wang, and Q. Zhang, ‘‘Extended Linear-Equation Ordered Statistics Decoding for Short Block Codes,” IEEE Internet of Things Journal, under revision, 2025.

  14. [WCL] C. Ma, Y. Peng, C. Wang, X. Zhuo, W. Wu, L. Tang, and Y. Zhao, ‘‘Multi-UAV Tracking under Partially Overlapping and Gapped Fields of View in Distributed Multi-sensor Networks,” IEEE Wireless Communications Letter, submission, 2025.

  15. [WCL] Y. Hu, X. Zhuo, C. Wang, L. Tang, Y. Zhao, and W. Wu, ‘‘Beamforming and Deployment Design for Cooperative AAV-enabled ISAC with Rate-Splitting Multiple Access under Imperfect CSI,” IEEE Wireless Communications Letter, submission, 2025.

Conference

  1. [MobiSys’26] B. Liu, Q. Yang, Y. Lu, J. Chauhan, W. Wu, and J. Zhang, ‘‘Rethinking Wireless Systems for LLM Workloads: Insights, Architecture, and Implementation,” in Proc. ACM MobiSys, submitted, 2025. [pdf]

  2. [ICASSP’26] H. Tu, W. Wu#, L. Li, L. Chen, and X. Chen, ‘‘FedMM: Dynamic Sample Selection for Multimodal Federated Learning,” in Proc. IEEE ICASSP, submitted, 2025.

  3. [ICC’26] Z. Mao, W. Wu#, F. Hu, and X. Shen, ‘‘Learning-Based Resource Management and Bitrate Adaptation for UAV Video Streaming over Low-Altitude Wireless Networks,” in Proc. IEEE ICC, submitted, 2025.

  4. [ICC’26] J. Cong, W. Wu#, C. You, Z. Mao, J. Huang, and C. Yu, ‘‘Diffusion-Based Data Augmentation and Resource Allocation for Heterogeneous Federated Learning,” in Proc. IEEE ICC, submitted, 2025.

  5. [ICC’26] X. Chen, W. Wu#, L. Li, F. Ji, P. Dong, and X. Shen, ‘‘FrozenSFL: Model-Frozen Split Federated Learning for LLM Fine-Tuning over Heterogeneous Devices,” in Proc. IEEE ICC, submitted, 2025.

  6. [ICC’26] Z. Li, W. Wu#, S. Wu, Y. Lu, and Y. Wang, ‘‘Energy-Efficient Split Fine-Tuning for Large Models on Edge Devices,” in Proc. IEEE ICC, submitted, 2025.

  7. [ICC’26] J. Huang, W. Wu#, L. Li, X. Chen, and H. Yu, ‘‘Adaptive Retransmission for Robust Split Federated Learning over Lossy Wireless Channels,” in Proc. IEEE ICC, submitted, 2025.

Journal & Magazine Papers

  1. [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,” Elsvier Computer Networks, to appear, 2025.

  2. [TMC’25] J. Chen, C. Yi, S. Gong, H. Du, W. Wu, J. Kang, and D. Niyato, ‘‘Generative AI-Aided QoE-Aware Resource Allocations for RlS-Assisted Digital Twin Interaction with Uncertain Evolution,” IEEE Transactions on Mobile Computing, to appear, 2025.

  3. [TCCN’25] 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, to appear, 2025.

  4. [TNSE’25] 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, to appear, 2025.

  5. [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, to appear 2025. [pdf]

  6. [Net’25] 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, 2025. [pdf]

  7. [TCCN’25] S. Xu, W. Yuan, L. Zheng, and W. Wu, ‘‘DTFIRNet: Deep learning-based Radar Perception for Urban Low-Altitude Wireless Networks,” IEEE Transactions on Cognitive Communications and Networking, to appear, 2025.

  8. [WCM’25] X. Xiong, B. Zheng, W. Wu#, W. Zhu, M. Wen, S. Lin, and Y. Zeng, ‘‘Intelligent Rotatable Antenna for Integrated Sensing, Communication, and Computation: Challenges and Opportunities,” IEEE Wireless Communications, to appear, 2025.

  9. [IoTJ’25] C. Wang, X. Zhuo, Y. Hu, W. Wu, L. Tang, Y. Zhao, F. Qu, and Z. Bu, ‘‘Performance Analysis of Satellite-Terrestrial Communication Network with Alamouti-based InterSatellite Cooperative Relay Protocol,” IEEE Internet of Things Journal, to appear, 2025. [pdf]

  10. [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, to appear, 2025. [pdf]

  11. [WCL’25] X. Xiong, B. Zheng, W. Wu, X. Shao, L. Dai, M. Zhao, and J. Tang, ‘‘Efficient Channel Estimation for Rotatable Antenna-Enabled Wireless Communication,” IEEE Wireless Communications Letter, vol. 14, no. 11, pp. 3719 - 3723, Nov. 2025. [pdf]

  12. [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]

  13. [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]

  14. [TCCN’25] Y. Hu, X. Zhuo, Z. Meng, W. Wu, W. Lu, L. Tang, F. Qu, and Z. Bu, ‘‘Collaborative Positioning Optimization for Multiple Moving Users in UAV-Enabled ISAC,” IEEE Transactions on Cognitive Communications and Networking, vol. 11, no. 5, pp. 3016 - 3030, Nov. 2025. [pdf]

  15. [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]

  16. [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]

  17. [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]

  18. [Net’25] S. Zou, M. Liwang, B. Wu, W. Wu, Y. Sun, and W. Ni, ‘‘Intent-Oriented Network Slicing with Hypergraphs,” IEEE Network, vol. 39, no. 4, pp. 202 - 210, July 2025. [pdf]

  19. [IoTJ’25] J. Lu, Y. Wang, J. Zhao, and W. Wu#, ‘‘Dynamic Data Collection for UAV-Assisted Green IIoT Constrained by Tail Distribution,” IEEE Internet of Things Journal, vol. 12, no. 13, pp. 22786 - 22799, July 2025. [pdf]

  20. [IoTJ’25] H. Jia, Y. Wang, W. Wu#, and J. Yuan, ‘‘Robust Transmission Design for Covert Satellite Communication Systems with Dual-CSI Uncertainty,” IEEE Internet of Things Journal, vol. 12, no. 12, pp. 21892 - 21903, June 2025. [pdf]

  21. [IoTJ’25] D. Li, S. Wu, Y. Wang, W. Wu, and Q. Zhang, “Intelligent Task Scheduling in Hybrid GEO-LEO Satellite-Assisted Marine IoT Network,” IEEE Internet of Things Journal, vol. 12, no. 7, pp. 8353-8367, Apr. 2025. [pdf]

  22. [IoTJ’25] X. Gao, H. Yin, Y. Sun, D. Wei, X. Xu, H. Chen, W. Wu, and S. Cui, “Multi-Level Feature Transmission in Dynamic Channels: A Semantic Knowledge Base and Deep Reinforcement Learning-Enabled Approach,” IEEE Internet of Things Journal, vol. 12, no. 8, pp. 10150-10162, Apr. 2025. [pdf]

  23. [IoTJ’25] L. Yu, W. Wu, and L. Mei, “A Lightweight Cross-layer Mutual Authentication with Key Agreement Protocol for IIoT,” IEEE Internet of Things Journal, vol. 12, no. 6, pp. 7051 - 7066, Mar. 2025. [pdf]

  24. [AI’2025] 程翔, 张颂歌, 卢永光, 李祖广, 王莹, 吴稳#, ‘‘面向低空智联网的智能资源管理关键技术,” 人工智能, vol. 1, pp. 15-25, Feb. 2025.

  25. [TNSE’25] J. Ren, D. Yang, K. Gong, W. Zhang, W. Chen, W. Wu#, and H. Zhang, “PTAS: PIFO-based Time-aware Shaper for Massive Concurrent Flows in Time-sensitive Networks,” Transactions on Network Science and Engineering, vol. 12, no. 1, pp. 83-95, Jan. 2025. [pdf]

  26. [WCM’24] J. Zheng, H. Luan, Y. Zhang, G. Li, Z. Su, and W. Wu, “Digital Twin in 6G: Embracing Comprehensive Network Intelligence,” IEEE Wireless Communications, vol. 31, no. 6, pp. 94 - 101, Dec. 2024. [pdf]

  27. [WCM’24] J. Cong, C. You, L. Chen, B. Zheng, Y. Liu, W. Wu, Y. Gong, S. Jin, and R. Zhang, ‘‘Near-field Integrated Sensing and Communication: Opportunities and Challenges,“ IEEE Wireless Communications, vol. 31, no. 6, pp. 162 - 169, Dec. 2024. [pdf]

  28. [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]

  29. [TWC’24] X. Zhuo, W. Wu, L. Tang, F. Qu, and X. Shen, “Value of Information-Based Packet Scheduling Scheme for AUV-Assisted UASNs,” IEEE Transactions on Wireless Communications, vol. 23, no. 7, pp. 7172 - 7185, July 2024. [pdf]

  30. [IoTJ’24] Z. Huang, P. Yang, C. Zhou, W. Wu, and N. Zhang, “Joint Sensing and Communication for mmWave VR in Metaverse: A Meta-Learning Approach,” IEEE Internet of Things Journal, vol. 11, no. 13, pp. 24049 - 24060, July 2024. [pdf]

  31. [IoTJ’24] H. Jia, Y. Wang, and W. Wu, “Dynamic Resource Allocation for Remote IoT Data Collection in SAGIN,” IEEE Internet of Things Journal, vol. 11, no. 11, pp. 20575 - 20589, June 2024. [pdf]

  32. [IoTJ’24] W. Jiang, B. Ai, M. Li, W. Wu, Y. Pei, and X. Shen, “Aerial IRSs Assisted Energy-Efficient Task Offloading and Computing,” IEEE Internet of Things Journal, vol. 11, no. 11, pp. 20178 - 20193, June 2024. [pdf]

  33. [WCL’24] X. Xiong, B. Zheng, L. Swindlehurst, J. Tang, and W. Wu, “A New Intelligent Reflecting Surface-Aided Electromagnetic Stealth Strategy,” IEEE Wireless Communications Letters, vol. 13, no. 5, pp. 1498 - 1502, May 2024. [pdf]

  34. [TMC’24] Z. Feng, X. Chen, Q. Wu, W. Wu, X. Zhang, and Q. Huang, “FedDD: Toward Communication-efficient Federated Learning with Differential Parameter Dropout”, IEEE Transaction on Mobile Computing, vol. 23, no. 5, pp. 5366 - 5384, May 2024. [pdf]

  35. [IoTJ’24] J. Xue, Y. Xu, W. Wu, T. Zhang, Q. Shen, H. Zhou, and W. Zhuang, “Sparse Mobile Crowdsensing for Cost-Effective Traffic State Estimation with Spatio-Temporal Transformer Graph Neural Network,” IEEE Internet of Things Journal, vol. 11, no. 9, pp. 16227-16242, May 2024. (IEEE ComSoc Best Readings) [pdf]

  36. [TWC’24] Z. Ma, W. Wu, F. Gao, and X. Shen, “Model-Driven Deep Learning for Massive Machine-Type Communications,” IEEE Transactions on Wireless Communications, vol. 23, no. 3, pp. 2197 - 2211, Mar. 2024. [pdf]

  37. [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]

  38. [IoTJ’24] J. Lin, P. Yang, W. Wu, N. Zhang, T. Han, and L. Yu, “Learning-Based Query Scheduling and Resource Allocation for Low-Latency Mobile Edge Video Analytics,“ IEEE Internet of Things Journal, vol. 11, no. 3, pp. 4872-4887, Jan. 2024. [pdf]

  39. [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. (ESI Highly Cited Paper) [pdf]

  40. [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]

  41. [TVT’23] K. Liu, W. Quan, N. Cheng, W. Wu, Z. Xu, L. Guo, D. Gao, and H. Zhang, “Reliable PPO-based Concurrent Multipath Transfer for Time-Sensitive Applications,” IEEE Transactions on Vehicular Technology, vol. 72, no. 10, pp. 13575 - 13590, Oct. 2023. [pdf]

  42. [IoTJ’23] W. Jiang, B. Ai, M. Li, W. Wu, and X. Shen, “Average Age of Information Minimization in Aerial IRS-Assisted Data Delivery,” IEEE Internet of Things Journal, vol. 10, np. 17, pp. 15133 - 15146, Sept. 2023. [pdf]

  43. [IoTJ’23] D. Han, Q. Ye, H. Peng, W. Wu, H. Wu, W. Liao, and X. Shen, “Two-Timescale Learning-Based Task Offloading for Remote IoT in Integrated Satellite-Terrestrial Networks”, IEEE Internet of Things Journal, vol. 10, no. 12, pp. 10131-10145, Jun. 2023. [pdf]

  44. [TWC’23] Z. Mao, F. Hu, W. Wu, H. Wu, and X. Shen, ‘‘Joint Distributed Beamforming and Backscattering for UAV-Assisted WPSNs,“ IEEE Transactions on Wireless Communications, vol. 22, no. 3, pp. 1510-1522, Mar. 2023. [pdf]

  45. [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. (ESI Highly Cited Paper) [pdf]

  46. [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. (Editor-in-Chief Invited Paper, Cover Paper, ESI Highly Cited Paper) [pdf]

  47. [TVT’22] R. Ding, J. Chen, W. Wu, J. Liu, F. Gao, and X. Shen, ‘‘Packet Routing in Dynamic Multi-Hop UAV Relay Network: A Multi-Agent Learning Approach,“ IEEE Transactions on Vehicular Technology, vol. 71, no. 9, pp. 10059-10072, Sep. 2022. [pdf]

  48. [IoTJ’22] Y. Wang, S. Wu, J. Jiao, W. Wu, Y. Wang, and Q. Zhang, ‘‘Age-Optimal Transmission Policy with HARQ for Freshness-Critical Vehicular Status Updates in Space-Air-Ground Integrated Networks,“ IEEE Internet of Things Journal, vol. 9, no. 8, pp. 5719-5729, Apr. 2022. [pdf]

  49. [NET’22] D. Yang, K. Gong, J, Ren, W. Zhang, W. Wu, and H. Zhang, ‘‘TC-Flow: Chain Flow Scheduling for Advanced Industrial Applications in Time-Sensitive Networks,“ IEEE Network Magazine, vol. 36, no. 2, pp. 16-24, Mar. 2022. [pdf]

  50. [TVT’22] D. Han, W. Liao, H. Peng, H. Wu, W. Wu, and X. Shen, ‘‘Joint Cache Placement and Cooperative Multicast Beamforming in Integrated Satellite-Terrestrial Networks,“ IEEE Transactions on Vehicular Technology, vol. 71, no. 3, pp. 3131–3143, Mar. 2022. [pdf, bib]

  51. [TWC’22] Z. Ma, W. Wu, M. Jian, F. Gao, and X. Shen, “Joint Constellation Design and Multiuser Detection for Grant-Free NOMA,” IEEE Transactions on Wireless Communications, vol. 21, no. 3, pp. 1973–1988, Mar. 2022. [pdf, bib]

  52. [TITS’22] D. Wang, P. Qi, Y. Zhao, C. Li, W. Wu, and Zan Li, ‘‘Covert Wireless Communication with Noise Uncertainty in Space-Air-Ground Integrated Vehicular Networks,“ IEEE Intelligent Transportation Systems Transactions, vol. 23, no. 3, pp. 2784-2797, Mar. 2022. [pdf]

  53. [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]

  54. [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]

  55. [JSAC’21] W. Zhang, D. Yang, W. Wu, H. Peng, N. Zhang, H. Zhang, and X. Shen, “Optimizing Federated Learning in Distributed Industrial IoT: A Multi-Agent Approach,” IEEE Journal on Selected Areas in Communications, vol. 39, no. 12, pp. 3688-3703, Dec. 2021. (ESI Highly Cited Paper) [pdf, bib]

  56. [TCC’21] Y. Chen, N. Zhang, Y. Zhang, X. Chen, W. Wu, and X. Shen, ‘‘Energy Efficient Dynamic Offloading in Mobile Edge Computing for Internet of Things,“ IEEE Transactions on Cloud Computing, vol. 9, no. 3, pp. 1050-1060, 2021. (ESI Hot Paper ) [pdf]

  57. [TCC’21] Y. Chen, N. Zhang, Y. Zhang, X. Chen, W. Wu, and X. Shen, ‘‘TOFFEE: Task Offloading and Frequency Scaling for Energy Efficiency of Mobile Devices in Mobile Edge Computing,“ IEEE Transactions on Cloud Computing, vol. 9, no. 4, pp. 1634-1644, 2021. (ESI Highly Cited Paper) [pdf]

  58. [IoTJ’21] C. Yu, W. Quan, D. Gao, Y. Zhang, K. Liu, W. Wu, H. Zhang, and X. Shen, ‘‘Reliable Cybertwin-Driven Concurrent Multipath Transfer with Deep Reinforcement Learning,“ IEEE Internet of Things Journal, vol. 8, no. 22, pp. 16207-16218, 2021. [pdf]

  59. [TVT’21] W. Zhang, D. Yang, H. Peng, W. Wu, W. Quan, H. Zhang, and X. Shen, ‘‘Deep Reinforcement Learning Based Resource Management for DNN Inference in Industrial IoT,“ IEEE Transactions on Vehicular Technology, vol. 70, no. 8, pp. 7605-7618, 2021. [pdf]

  60. [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. (ESI Highly Cited Paper) [pdf, bib]

  61. [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. (Editor-in-Chief Invited Paper, IEEE Vehicular Technology Society OJVT Best Paper Award) [pdf]

  62. [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]

  63. [TCCN’20] S. Gu, Y. Wang, N. Wang, and W. Wu, ‘‘Intelligent Optimization of Availability and Communication Cost in Satellite-UAV Mobile Edge Caching System with Fault-Tolerant Codes,“ IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 4, pp. 1230-1241, 2020. [pdf]

  64. [TVT’20] M. Gao, B. Ai, Y. Niu, W. Wu, P. Yang, F. Lyu, and X. Shen, ‘‘Efficient Hybrid Beamforming with Anti-Blockage Design for High-Speed Railway Communications,“ IEEE Transactions on Vehicular Technology, vol. 69, no. 9, pp. 9643-9655, 2020. [pdf]

  65. [TII’20] P. Yang, F. Lyu, W. Wu, N. Zhang, L. Yu, and X. Shen, ‘‘Edge Coordinated Query Configuration for Low-Latency and Accurate Video Analytics,“ IEEE Transactions on Industrial Informatics, vol. 16, no. 7, pp. 4855-4864, 2020. [pdf]

  66. [TCCN’20] Y. Tang, P. Yang, W. Wu, J. W. Mark, and X. Shen, ‘‘Interference Mitigation via Cross-Tier Cooperation in Heterogeneous Cloud Radio Access Networks,“ IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 1, pp. 201-213, 2020. [pdf]

  67. [TWC’20] K. Aldubaikhy, W. Wu, Q. Ye, and X. Shen, “Low-Complexity User Selection Algorithm for Multiuser Transmission in mmWave WLANs,” IEEE Transactions on Wireless Communications, vol. 19, no. 4, pp. 2397-2410, Apr. 2020. [pdf, bib]

  68. [WCM’20] K. Aldubaikhy, W. Wu, N. Zhang, N. Cheng, and X. Shen, “mmWave IEEE 802.11ay for 5G Fixed Wireless Access,” IEEE Wireless Communications Magazine, vol. 27, no. 2, pp. 88-85, Apr. 2020. [pdf, bib]

  69. [NET’20] B. Zheng, M. Wen, S. Lin, W. Wu, F. Chen, F. Ji, and H. Yu, ‘‘Design of Multi-Carrier LBT for LAA&WiFi Coexistence in Unlicensed Spectrum,“ IEEE Network, vol. 34, no. 1, pp. 76-83, 2020. [pdf]

  70. [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]

  71. [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]

  72. [TVT’19] Y. Tang, N. Cheng, W. Wu, Y. Dai, M. Wang, and X. Shen, “Delay-Minimization Routing for Heterogeneous VANETs with Machine Learning based Mobility Prediction,” IEEE Transactions on Vehicular Technology, vol. 68, no. 4, pp. 3967-3979, Apr. 2019. [pdf, bib]

  73. [IOTJ’19] X. Liu, Y. Liu, N. Zhang, W. Wu, and A. Liu, ‘‘Optimizing Trajectory of Unmanned Aerial Vehicles for Efficient Data Acquisition: A Matrix Filling Approach,“ IEEE Internet of Things Journal, vol. 6, no. 2, pp. 1829-1840, 2019. (ESI Highly Cited Paper) [pdf]

  74. [ACCESS’19] R. Ding, Y. Xu, F. Gao, X. Shen, and W. Wu, ‘‘Deep Reinforcement Learning for Router Selection in Network with Heavy Traffic,“ IEEE Access, vol. 7, pp. 37109-37120, 2019. [pdf]

Conference Papers

  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. [WCSP’25] S. Zhang, W. Wu#, S. Wu, W. Yuan, L. Song, and X. Shen, ‘‘Collaborative LLM Inference over LEO Satellite Networks: Model Splitting and Pipeline Parallelism," in Proc. IEEE WCSP, Chongqing, China, Oct. 23-25, 2025.

  3. [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. (Mobicom Workshop Best Paper Award )

  4. [Mobicom Demo’25] Z. Li, D. Ou, W. Wu#, S. Zhang, S. Wu, and X. Shen, ‘‘Demo: Split-and-Pipeline: Collaborative Large Model Inference on Edge Devices," in Proc. ACM MobiCom Demo, Hong Kong, Nov. 4-8, 2025.

  5. [Globecom’25] X. Cheng, Z. Mao, Y. Wang, and W. Wu#, ‘‘Diffusion-Based Reinforcement Learning for Efficient Task Scheduling in CAV Network," in Proc. IEEE Globecom, Taibei, Taiwan, 2025.

  6. [Globecom’25] X. Yu, D. Li, B. Gu, X. Jing, W. Wu, T. Wu, and K. Yu, ‘‘Meta-Learning Driven Lightweight Phase Shift Compression for IRS-Assisted Wireless Systems," in Proc. IEEE Globecom, Taibei, Taiwan, 2025.

  7. [ICCC’25] S. Xu, L. Zheng, and W. Wu, ‘‘Deep Delay-Parameter-Aware Radar Perception for Urban Low-Altitude Wireless Networks" in Proc. IEEECIC ICCC Workshop/, Shanghai, China, Aug. 10-13, 2025.

  8. [ICCC’25] S. Li, W. Wu#, J. Cong, Z. Mao, L. Li, Y. Hu, and C. Chen ‘‘Efficient Handover Authentication in Digital Twin Assisted Networks" in Proc. IEEE/CIC ICCC, Shanghai, China, Aug. 10-13, 2025.

  9. [IJCAI’25] J. Huang, M. Wu, P. Li, W. Wu, and R. Yu, ‘‘VimGeo: Efficient Cross-View Geo-Localization with Vision Mamba Architecture," in Proc. IJCAI, Montreal, Canada, Aug. 16-22, 2025.

  10. [INFOCOM’25 Workshop] J. Cong, W. Wu#, G. Cheng, C. You, X. Huang, and X. Chen, ‘‘Data Enhanced Edge Incremental Learning and Resource Allocation over Wireless Network," in Proc. IEEE INFOCOM Workshop, London, UK, May 19–22, 2025.

  11. [INFOCOM’25 Workshop] X. Chen, L. Li, F. Ji, and W. Wu, ‘‘Memory-Efficient Split Federated Learning for LLM Fine-Tuning on Heterogeneous Mobile Devices,“ in Proc. IEEE INFOCOM Workshop, London, UK, May 19–22, 2025. [pdf]

  12. [ICC’25] Y. Wang, K. Qu, W. Wu#, and X. Shen, ‘‘Edge-Assisted Accelerated Cooperative Sensing for CAVs: Task Placement and Resource Allocation,” in Proc. IEEE ICC, Montreal, Canada, June 8–12, 2025. [pdf]

  13. [ICC’25] L. Li, X. Chen, and W. Wu#, ‘‘RingAda: Pipelining Large Model Fine-Tuning on Edge Devices with Scheduled Layer Unfreezing,” in Proc. IEEE ICC, Montreal, Canada, June 8–12, 2025. [pdf]

  14. [Globecom’24] S. Zhang, G. Cheng, Z. Li, and W. Wu#, “SplitLLM: Hierarchical Split Learning Scheme for Large Model over Wireless Network,” in Proc. IEEE Globecom Workshop, Cape Town, South Africa, Dec. 8-12, 2024. [pdf]

  15. [Globecom’24] H. Tu, L. Chen, Z. Li, X. Chen, and W. Wu#, “Mobility-Aware Federated Learning: Multi-armed Bandit Based Selection in Vehicular Network,” in Proc. IEEE Globecom Workshop, Cape Town, South Africa, Dec. 8-12, 2024. [pdf]

  16. [Globecom’24] K. Shang, S. Liu, J. Tang, X. Cheng, W. Wu#, and L. Song, “Joint Slice Switching and Resource Allocation for Energy-Efficient Network Slicing,” in Proc. IEEE Globecom, Cape Town, South Africa, Dec. 8-12, 2024.

  17. [Globecom’24] X. Shi, G. Li, H. Luan, Z. Su, S. Yu, and W. Wu , “Towards Scalable and Privacy-preserving Data Sharing in Internet of Digital Twins,” in Proc. IEEE Global Communications Conference (Globecom), Cape Town, South Africa, Dec. 8-12, 2024.

  18. [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]

  19. [INFOCOM Workshop’24] Z. Li, W. Wu#, S. Wu, and W. Wang, “Adaptive Split Learning and Resource Allocation over Energy-Constrained Wireless Edge Networks,” in Proc. IEEE INFOCOM Workshop, Vancouver, Canada, May 20–23, 2024. [pdf]

  20. [ICC’24] S. Liu, W. Wu#, S. Li, T. Luan, and N. Zhang, “Digital Twin-Assisted Adaptive Preloading for Short Video Streaming,” in Proc. IEEE ICC, Denver, CO, USA, June 9-13, 2024. [pdf]

  21. [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. (Distinguished Paper Award ) [pdf]

  22. [VTC-Fall’23] Y. Hu, L. Tang, X. Zhuo, Z. Li, W. Wu, Y. Zhao, and Z. Bu, “Imaging Based on Communication-Assisted Sensing for UAV-Enabled ISAC”, in Proc. IEEE Vehicular Technology (VTC) Fall, Hong Kong, 2023. [pdf]

  23. [Globecom’23] X. Zhuo, T. Hu, W. Wu#, L. Tang, F. Qu, and X. Shen, “Multi-AUV Collaborative Data Collection in Integrated Underwater Acoustic Communication and Detection Networks,” in Proc. IEEE Global Communications Conference (Globecom), Kuala Lumpur, Malaysia, 2023. [pdf]

  24. [ICCC’23] S. Zhang, H. Tu, Z. Li, S. Liu, S. Li, W. Wu, and X. Shen, ‘‘Cluster-HSFL: A Cluster-Based Hybrid Split and Federated Learning“, in Proc. IEEE ICCC, Dalian, China, 2023. [pdf]

  25. [ICCC’23] Y. Guo, X. Zhuo, L. Tang, W. Wu, Y. Wei, and F. Qu, ‘‘Neighbor Discovery with Directional Transmission in Integrated Underwater Acoustic Communication and Detection Networks],“ in Proc. IEEE/CIC International Conference on Communications in China (ICCC) Workshop, Dalian, China, 2023. [pdf]

  26. [ICCC’23] Y. Wu, X. Zhuo, L. Tang, W. Wu, and F. Qu, ‘‘Cooperative Coverage Path Planning for AUVs in Integrated Underwater Acoustic Communication and Detection Networks,“ in Proc. IEEE/CIC International Conference on Communications in China (ICCC), Dalian, China, 2023. [pdf]

  27. [PIMRC’23] Z. Huang, P. Yang, W. Wu, and N. Zhang, “Predictive and Robust Field-Of-View Selection for Virtual Reality Video Streaming,” in Proc. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Toronto, Canada, 2023. [pdf]

  28. [PIMRC’23] Q. Li, W. Wu, W. Zhang, and X. Shen, “Traffic Prediction in Multi-RAT Heterogeneous Network: A User-Cybertwin Asychronized Learning Approach,” in Proc. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Toronto, Canada, 2023. [pdf]

  29. [BSC’23] S. Liu, W. Wu, L. Fu, K. Qu, Q. Ye, W. Zhuang, and X. Shen, “Millimeter Wave Full-Duplex Networks: MAC Design and Throughput Optimization,” in Proc. IEEE Biennial Symposium on Communications (BSC), Montreal, Canada, July 4-7, 2023. [pdf]

  30. [BSC’23] J. Hou, P. Yang, T. Qin, and W. Wu, “Edge-Coordinated Collaborative Perception for Connected Autonomous Vehicles Using Point Cloud,” in Proc. IEEE Biennial Symposium on Communications (BSC), Montreal, Canada, July 4-7, 2023. [pdf]

  31. [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]

  32. [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]

  33. [ICC’23] S. Li, W. Wu#, Y. Meng, J. Li, H. Zhu, and X. Shen, “Data Poisoning Attack against Anomaly Detectorsin Digital Twin-Based Networks,” in Proc. IEEE International Conference on Communications (ICC), Rome, Italy, May 28- June 1, 2023. [pdf]

  34. [ICC’23] X. Zhuo, W. Wu#, L. Tang, F. Qu, and X. Shen, “Value of Information-Based Packet Scheduling forAUV-Assisted UASNs,” in Proc. IEEE International Conference on Communications (ICC), Rome, Italy, May 28- June 1, 2023. [pdf]

  35. [ICC’23] X. Huang, M. Li, W. Wu#, C. Zhou, and X. Shen, “Digital Twin-Assisted Collaborative Transcoding for Better User Satisfaction in Live Streaming,” in Proc. IEEE International Conference on Communications (ICC), Rome, Italy, May 28- June 1, 2023. [pdf]

  36. [GLOBECOM’22] X. Huang, C. Zhou, W. Wu, M. Li, H. Wu, and X. Shen, “Personalized QoE Enhancement for Adaptive Video Streaming: A Digital Twin-Assisted Scheme,” in Proc. IEEE GLOBECOM, Rio de Janeiro, Brazil, Dec. 4-8, 2022. [pdf]

  37. [GLOBECOM’22] J. Xue, T. Zhang, W. Wu, H. Zhou, and X. Shen, ‘‘Sparse Big Data for Vehicular Network Traffic Flow Estimation: A Machine Learning Approach,“ in Proc. IEEE GLOBECOM, Rio de Janeiro, Brazil, Dec. 4-8, 2022. [pdf]

  38. [GLOBECOM’22] C. Wang, P. Yang, J. Lin, W. Wu, and N. Zhang, ‘‘Object-Based Resolution Selection for Efficient Edge-Assisted Multi-Task Video Analytics,“ in Proc. IEEE GLOBECOM, Rio de Janeiro, Brazil, Dec. 4-8, 2022. [pdf]

  39. [ICC’22] J. Chen, R. Ding, W. Wu, J. Liu, F. Gao, and X. Shen, ‘‘Multi-Agent Learning Based Packet Routing in Multi-Hop UAV Relay Network“, in Proc. IEEE ICC, Seoul, South Korea, May 16–20, 2022. [pdf]

  40. [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. (Best Paper Award ) [pdf]

  41. [HPCC’21] E. Cui, W. Zhang, D. Yang, W. Wu, and F. Lyu, ‘‘Resource-Efficient DNN Training and Inference for Heterogeneous Edge Intelligence in 6G,“ in Proc. IEEE HPCC Workshop, Haiko, China, Dec. 20-22, 2021. [pdf]

  42. [GLOBECOM’21] Z. Mao, F. Hu, Q. Li, W. Wu, and X. Shen, ‘‘Joint Distributed Beamforming and Backscatter Cooperation for UAV-Assisted WPSNs“, in Proc. IEEE GLOBECOM, Madrid, Spain, Dec. 7–11, 2021. [pdf]

  43. [GLOBECOM’21] C. Zhou, H. Wu, M. He, W. Wu, N. Cheng, and X. Shen, ‘‘Adaptive Access Mode Selection in Space-Ground Integrated Vehicular Networks“, in Proc. IEEE GLOBECOM, Madrid, Spain, Dec. 7–11, 2021. [pdf]

  44. [MASS’21] J. Lin, P. Yang, W. Wu, N. Zhang, T. Han, and L. Yu, ‘‘Edge Learning for Low-Latency Video Analytics: Query Scheduling and Resource Allocation“, in Proc. IEEE MASS, Auburn, United States, Oct. 4–7, 2021. [pdf]

  45. [ICCC’21] Z. Huang, P. Yang, N. Zhang, F. Lyu, Q. Li, W. Wu, and X. Shen, ‘‘QoE-driven Mobile 360 Video Streaming: Predictive View Generation and Dynamic Tile Selection“, in Proc. IEEECIC ICCC/, Xiamen, China, Jul. 28-30, 2021. [pdf]

  46. [ICC’21] Z. Ma, W. Wu, F. Gao, and X. Shen, “Multi-Task Learning Aided Joint Constellation Design and Multiuser Detection for GF-NOMA,” in Proc. IEEE ICC, Montreal, Canada, June 14-23, 2021. [pdf, bib]

  47. [ICC’21] W. Zhang, D. Yang, W. Wu, H. Peng, W. Quan, H. Zhang, and X. Shen, ‘‘Spectrum and computing resource management for federated learning in distributed industrial IoT“, in Proc. IEEE ICC Workshop, Montreal, Canada, June 14-23, 2021. [pdf]

  48. [GLOBECOM’20] W. Zhang, D. Yang, H. Peng, W. Wu, W. Quan, H. Zhang, and X. Shen, ‘‘Deep Reinforcement Learning Based Resource Management for DNN Inference in IIoT“, in Proc. IEEE GLOBECOM, Taipei, Taiwan, Dec. 7-11, 2020. [pdf]

  49. [ICC’20] W. Wang, C. Zhou, H. He, W. Wu, W. Zhuang, and X. Shen, ‘‘Cellular Traffic Load Prediction with LSTM and Gaussian Process Regression“, in Proc. IEEE ICC, Virtual Conference, Jun. 7-11, 2020. [pdf]

  50. [GLOBECOM’19] C. Zhou, W. Wu, H. He, P. Yang, F. Lyu, N. Cheng, and X. Shen, “Delay-aware IoT Task Scheduling in Space-air-ground Integrated Network,” in Proc. IEEE GLOBECOM, Waikoloa, HI, USA, 2019. [pdf]

  51. [GLOBECOM’19] M. Gao, B. Ai, Y. Niu, W. Wu, P. Yang, F. Lyu, and X. Shen, ‘‘Edge Caching and Content Delivery with Minimized Delay for both High-Speed Train and Local Users“, in Proc. IEEE GLOBECOM, Waikoloa, United States, Dec. 9–13, 2019. [pdf]

  52. [WCSP’19] C. Zhou, H. He, P. Yang, F. Lyu, N. Cheng, W. Wu, and X. Shen, ‘‘Deep RL-based Trajectory Planning for AoI Minimization in UAV-assisted IoT“, in Proc. IEEE WCSP, Xi'an, China, Oct. 23–25, 2019. [pdf]

  53. [ICC’19] M. Gao, B. Ai, Y. Niu, W. Wu, P. Yang, F. Lyu, and X. Shen, ‘‘On Hybrid Beamforming of mmWave MU-MIMO System for High-Speed Railways“, in Proc. IEEE ICC, Shanghai, China, May 20–24, 2019. [pdf]

  54. [ICC’19] Y. Tang, P. Yang, W. Wu, J. W. Mark, and X. Shen, ‘‘Cooperation-based Interference Mitigation in Heterogeneous Cloud Radio Access Networks“, in Proc. IEEE ICC, Shanghai, China, May 20–24, 2019. (Invited for fast-track journal publication in IEEE Transactions on Cognitive Communications and Networking) [pdf]

  55. [ICC’19] F. Lyu, P. Yang, W. Shi, H. Wu, W. Wu, N. Cheng, and X. Shen, ‘‘Online UAV Scheduling Towards Throughput QoS Guarantee for Dynamic IoVs“, in Proc. IEEE ICC, Shanghai, China, May 20–24, 2019. [pdf]

  56. [GLOBECOM’18] K. Aldubaikhy, W. Wu, and X. Shen, “BF-PDVG: Hybrid Beamforming and User Selection for UL MU-MIMO mmWave Systems,” in Proc. IEEE Globecom Workshop, Abu Dhabi, United Arab Emirates, 2018. [pdf]

  57. [WiOpt’18] W. Wu, Q. Shen, K. Aldubaikhy, N. Cheng, N. Zhang, and X. Shen, “Enhance the edge with beamforming: Performance analysis of beamforming-enabled WLAN,” in Proc. IEEE WiOpt, Shanghai, China, 2018. [pdf, bib]

  58. [ICC’17] W. Wu, Q. Shen, M. Wang, and X. Shen, “Performance Analysis of IEEE 802.11.ad Downlink Hybrid Beamforming,” in Proc. IEEE ICC, Paris, France, 2017. [pdf, bib]

  59. [ICCC’17] K. Aldubaikhy, Q. Shen, M. Wang, W. Wu, X. Shen, O. Aboul-Magd, Y. Xin, R. Sun, and E. Au, ‘‘MAC Layer Design for Concurrent Transmissions in Millimeter Wave WLANs“, in Proc. IEEE/CIC International Conference on Communications in China, Qingdao, China, Oct. 22–24, 2017. [pdf]

  60. [ICCCN’14] W. Wu, X. Li, H. Yin, C. Zhang, and G. Wei, “A Joint Real Grassmannian Quantization Strategy for MIMO Interference Alignment with Limited Feedback,” in Proc. IEEE ICCCN, Shanghai, China, Aug. 4-7, 2014. [pdf]

  61. [PIMRC’14] W. Wu, X. Li, H. Yin, C. Zhang, and G. Wei, ‘‘A Joint Real Grassmannian Quantization Strategy for SISO IA with Limited Feedback,“ in Proc. IEEE PIMRC, Washington, USA, Sep. 2-5, 2014. [pdf]

Demos

  1. S. Zhang, Z. Li, H. Tu, S. Liu, and W. Wu, “Cluster-HSFL: A Cluster-based Hybrid Split and Federated Learning Architecture”, in Proc. IEEE ComSoc Frontier Networking Symposium, to appear, 2023. [video]

  2. X. Wang, S. Li, W. Wu, H. Zhu, and X. Shen, “Yes, One-Bit-Flip Matters! Universal DNN Model Inference Depletion with Runtime Code Fault Injection”, 2023. [video]

Patents

PCT Patents

  1. Inventors: 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]

  2. Inventors: W. Zhuang, K. Qu, W. Wu, M. Li, X. Shen, and X. Li, ‘‘Systems and Methods for AI Inference“. United States, App. 19,077,680, 2025/03/12. Patent Status: Granted/Issued. Year Issued: 2025/06/26. [pdf]

  3. Inventors: X. Shen, W. Wu, M. Li, K. Qu, C. Zhou, W. Zhuang, and X. Li, “Systems and Methods for Cluster-Based Parallel Split Learning”. Canada, International application number: PCT/CA2022/050487, 2022/03/30. Patent Status: Pending.

  4. Inventors: W. Zhuang, K. Qu, W. Wu, M. Li, X. Shen, and X. Li, ‘‘Systems and Methods for AI Inference". Canada, International Application Number: PCT/CA2022/051493, 2022/10/12. Patent Status: Pending.

  5. Inventors: L. Li, W. Wu, “ A Memory-Efficient System and Method for Fine-Tuning Large Models on Edge Devices.” United States, PCT/CN2024/136837, 2024/12/16. Patent Status: Pending.

  6. Inventors: L. Li, W. Wu, X. Chen, “Systems and Methods for Collaborative Fine-Tuning Large Models Based on On-Demand Parameter Activation.” United States, PCT/CN2024/129871, 2024/11/5. Patent Status: Pending.

  7. Inventors: W. Wu, K. Shang, J. Tang, Z. Mao, “Systems and Methods for Energy-Efficient Network Slicing Switch and Resource Management .” United States, PCT/CN2025/096426, 2025/5/22. Patent Status: Pending.

China Patents

  1. 发明人: 吴稳, 陈小培, 李靓, “一种基于模型冻结和模型共享的大模型分布式微调方法与系统.” 中国发明专利, 申请中.

  2. 发明人: 吴稳, 李祖广, 吴绍华, 张颂歌, 王野, “一种基于图论的快速AI模型分割方法与系统.” 中国发明专利, 申请中.

  3. 发明人: 吴稳, 蔡张华, “远场天线辐射方向图确定方法、装置、设备、存储介质及产品.” 中国发明专利, 202511801080.5, 2025-12-02, 申请中.

  4. 发明人: 徐帅, 袁伟杰, 吴稳, 蔡云龙, “雷达回波时延预测方法、装置、设备、存储介质及产品.” 中国发明专利, 202511754511.7, 2025-11-26, 申请中.

  5. 发明人: 吴稳, 屠昊宇, 李靓, 陈林, 陈旭, “基于移动感知的车载联邦学习优化方法及系统.” 中国发明专利, 202511664911.9, 2025-11-13, 申请中.

  6. 发明人: 李靓, 吴稳, 房善想, “基于动态子网络调度的联邦学习方法及系统.” 中国发明专利, 202511391713.X, 2025-09-26, 申请中.

  7. 发明人: 吴稳, 尚柯源, 唐建华, 毛执, “网络切片管理方法、装置、设备、存储介质及产品.” 中国发明专利, 202510583355.6, 2025-05-07, 申请中.

  8. 发明人: 蔡张华, 吴稳, “一种相位中心测量方法.” 中国发明专利, 202411949589.X, 2024/12/27, 申请中.

  9. 发明人: 李靓, 吴稳, “大模型微调训练方法、装置、设备、存储介质及产品.” 中国发明专利, 202411772769.5, 2024/12/4, 公开.

  10. 发明人: 李靓, 吴稳, 陈小培, “大模型调整方法、装置、设备及存储介质.” 中国发明专利, 202411568558.X, 2024/11/5, 申请中.

  11. 发明人: 陈珉, 李少锋, 罗霄, 任志强, 吴稳, “一种基于Kubernetes和强化学习框架的车联网资源调度系统及方法.” 中国发明专利, 202311665165.6, 20231115, 实审中.

  12. 发明人: 杨鹏, 黄芷璇, 吴稳, “一种基于VR用户视点轨迹的毫米波接入点选择方法及系统.” 中国发明专利, 202210819036.7, 2024/03/21, 已授权.

  13. 发明人: 林彬, 胡旭, 卫海超, 吴稳, 吴绍华, 王伟志, “基于低轨卫星星座的端到端通信性能解析模型建立方法.” 中国发明专利, 202310488511.1, 2023/12/25, 已授权.

China Softwares

  1. 发明人: 任志强, 李少锋, 罗霄, 陈珉, 吴稳, 代明军, “基于Kubernetes的车联网资源分配管控软件 V1.0.“ 中国软件著作, 2024SR1553334, 20241018，已授权.

Editorial

  1. Y. Zhang, F. Lyu, P. Yang, W. Wu, and J. Gao (guest editors), “IoT Intelligence Empowered by End-Edge-Cloud Orchestration,” China Communications, vol. 19, no. 7, pp. 152-156, July 2022. (CAS Q3) [pdf]

Standards and White Papers

  1. 基于卫星网络的传算协同研究/Research on Transmission-Computing Collaboration for Satellite Networks, 中国通信标准化协会，TC12 WG4, ongoing, leading, Jun. 2025 - Jun. 2027

  2. IEEE Standard P2805.4 - Edge Collaboration Protocols for Federated Learning，ongoing, participant, 2022 - 2026. [link]

  3. 超级自动化平台技术能力框架通用要求/General Requirements for Hyperautomation Platform Technical Capability, 中国人工智能产业发展联盟标准, participant, AIIA/PG 0002-2023, Oct. 2023. [pdf]

  4. 数字孪生网络实践与启示研究报告/Report for Digital Twin Network: Practices and Insightsgital Twin Network: Practices and Insights, 6G ANA, participant, pp. 1-62, Oct. 2024 [link]

  5. 新一代移动通信系统的智能服务质量评估和保障方法研究/Research on Assessment and Assurance Methods for Quality of ArtiCommunication Systems, 中国通信标准化协会，CCSA, ongoing, participant, Feb. 2024 - Feb. 2026