Dr. Dingzhu Wen

Dr. Dingzhu Wen

Assistant Professor ShanghaiTech University

Journal Papers

Topic 1: Integrated Sensing-Communication-Computation (ISCC)

  1. D. Wen, P. Liu, G. Zhu, Y. Shi, J. Xu, Y. C. Eldar, and S. Cui, “Task-Oriented Sensing, Computation, and Communication Integration for Multi-Device Edge AI,” IEEE Trans. Wireless Commun., vol. 23, no. 3, pp. 2486-2502, Mar. 2024, doi: 10.1109/TWC.2023.3303232. (ESI Highly Cited Paper, Related Code: https://github.com/PeixiLiu/humanMotionRadar)
  2. S. Liu, D. Wen, D. Li, Q. Chen, G. Zhu, and Y. Shi, “Energy-Efficient Optimal Mode Selection for Edge AI Inference via Integrated Sensing-Communication-Computation,” in IEEE Trans. Mobile Comput., vol. 23, no. 12, pp. 14248-14262, Dec. 2024, doi: 10.1109/TMC.2024.3440581. (Corresponding Author)
  3. D. Wen, X. Li, Y. Zhou, Y. Shi, S. Wu, C. Jiang, “Integrated Sensing-Communication-Computation for Edge Artificial Intelligence,” IEEE Internet Things Mag., vol. 7, no. 4, pp. 14-20, Jul. 2024, doi: 10.1109/IOTM.001.2300146.
  4. D. Wang, D. Wen, Y. He, Q. Chen, G. Zhu, and G. Yu, “Joint Device Scheduling and Resource Allocation for ISCC-Based Multi-View-Multi-Task Inference,” in IEEE Internet Things J., doi: 10.1109/JIOT.2024.3456569. (Corresponding Author)
  5. Z. Zhuang, D. Wen, Y. Shi, G. Zhu, S. Wu, and D. Niyato, “Integrated Sensing-Communication-Computation for Over-the-Air Edge AI Inference,” IEEE Trans. Wireless Commun., vol. 23, no. 4, pp. 3205-3220, Apr. 2024, doi: 10.1109/TWC.2023.3306465. (Co-Corresponding Author)
  6. D. Wen, Y. Zhou, X. Li, Y. Shi, K. Huang, and K. B. Letaief, “A Survey on Sensing, Communication, and Computation,” submitted to IEEE Commun. Surv. Tut., 2024.

Topic 2: Task-Oriented and Semantic Communications

  1. X. Jiao, D. Wen, G. Zhu, W. Jiang, W. Luo, and Y. Shi, “Task-Oriented Over-the-Air Computation for Edge-Device Co-inference with Balanced Classification Accuracy,” in IEEE Trans. Veh. Technol., vol. 73, no. 11, pp. 17818-17823, Nov. 2024, doi: 10.1109/TVT.2024.3422418. (Co-Corresponding Author)
  2. D. Wen, X. Jiao, P. Liu, G. Zhu, Y. Shi, and K. Huang, “Task-Oriented Over-the-Air Computation for Multi-Device Edge AI,” IEEE Trans. Wireless Commun., vol. 23, no. 3, pp. 2039-2053, Mar. 2024, doi: 10.1109/TWC.2023.3294703.
  3. P. Zhang, D. Wen, G. Zhu, Q. Chen, K. Han, and Y. Shi, “Collaborative Edge AI Inference over Cloud-RAN,” IEEE Trans. Commun., vol. 72, no. 9, pp. 5641-5656, Sept. 2024, doi: 10.1109/TCOMM.2024.3388488. (Corresponding Author)
  4. P. Yang, D. Wen, Q. Zeng, Y. Zhou, T. Wang, H. Cai, and Y. Shi, “Over-the-Air Computation Empowered Vertically Split Inference,” in IEEE Trans. Wireless Commun., doi: 10.1109/TWC.2024.3485678. (Co-Corresponding Author)
  5. Z. Hu, C. You, T. Liu, D. Wen, Y. Hu, Y. Cui, Y. Gong, and K. Huang, “Semantic Communication Meets Edge Intelligence: Semantic-Relay-Aided Text Transmissions,” in IEEE Internet Things J., doi: 10.1109/JIOT.2024.3433431.
  6. Y. Shi, Y. Zhou, D. Wen, Y. Wu, C. Jiang, and K. B. Letaief, “Task-Oriented Communications for 6G: Vision, Principles, and Technologies,” IEEE Wireless Commun., vol. 30, no. 3, pp. 78-85, Jun. 2023, doi: 10.1109/MWC.002.2200468.
  7. Q. Lan, D. Wen, Z. Zhang, Q. Zeng, X. Chen, P. Popovski, and K. Huang, “What is Semantic Communication? A View on Conveying Meaning in the Era of Machine Intelligence,” J. Commun. Inf. Netw., vol. 6, no. 4, pp. 336 – 371, Dec. 2021, doi: 10.23919/JCIN.2021.9663101.

Topic 3: Edge Machine Learning

  1. S. Liu, C. Liu, D. Wen, and G. Yu, “Efficient Collaborative Learning Over Unreliable D2D Network: Adaptive Cluster Head Selection and Resource Allocation,” in IEEE Trans. Commun., doi: 10.1109/TCOMM.2024.3435072. (Corresponding Author)
  2. P. Yang, Y. Jiang, D. Wen, T. Wang, C. N. Jones, Y. Shi, “Decentralized Over-the-Air Federated Learning by Second-Order Optimization Method,” IEEE Trans. Wireless Commun., vol. 23, no. 6, pp. 5632-5647, June 2024, doi: 10.1109/TWC.2023.3327610. (Co-Corresponding Author)
  3. L. Zeng, D. Wen, G. Zhu, C. You, Q. Chen, and Y. Shi, “Federated Learning with Energy Harvesting Devices,” IEEE Trans. Green Commun. Netw., vol.8, no. 1, pp. 190-204, Mar. 2024, doi: 10.1109/TGCN.2023.3310569. (Corresponding Author)
  4. S. Liu, G. Yu, D. Wen, X. Chen, M. Bennis, and H. Chen, “Communication and Energy Efficient Decentralized Learning over D2D Networks,” IEEE Trans. Wireless Commun., vol. 22, no.12, pp. 9549-9563, Dec. 2023, doi: 10.1109/TWC.2023.3271854. (Corresponding Author)
  5. D. Wen, K.-J. Jeon, and K. Huang, “Federated Dropout – A Simple Approach for Enabling Federated Learning on Resource Constrained Devices,” IEEE Wireless Commun. Lett., vol. 11, no. 5, pp. 923-927, May 2022, doi: 10.1109/LWC.2022.3149783.
  6. D. Wen, K.-J. Jeon, M. Bennis, and K. Huang, “Adaptive Subcarrier, Parameter, and Power Allocation for Partitioned Edge Learning over Broadband Channels”, IEEE Trans. Wireless Commun., vol. 20, no. 12, pp. 8348-8361, Dec. 2021, doi: 10.1109/TWC.2021.3092075.
  7. D. Wen, M. Bennis, and K. Huang, “Joint Parameter-and-Bandwidth Allocation for Improving the Efficiency of Partitioned Edge Learning,” IEEE Trans. Wireless Commun., vol. 19, no. 12, pp. 8272-8286, Dec. 2020, doi: 10.1109/TWC.2020.3021177.
  8. D. Wen, X. Li, Q. Zeng, J. Ren, and K. Huang, “An Overview of Data-Importance Aware Radio Resource Management for Edge Machine Learning,” J. Commun. Inf. Netw., vol. 4, no. 4, pp. 1–14, Dec. 2019, doi: 10.23919/JCIN.2019.9005429.
  9. Y. Chen, S. Liu, and D. Wen, “Communication Efficient Decentralized Learning over D2D Network: Adaptive Relay Selection and Resource Allocation,” in IEEE Wireless Commun. Lett., vol. 13, no. 9, pp. 2362-2366, Sept. 2024, doi: 10.1109/LWC.2024.3412674.
  10. Q. Chen, Z. You, D. Wen, and Z. Zhang, “Enhanced Hybrid Hierarchical Federated Edge Learning Over Heterogeneous Networks,” IEEE Trans. Veh. Technol., vol. 72, no. 11, pp. 14601-14614, Nov. 2023, doi: 10.1109/TVT.2023.3287355.
  11. Y. Wang, D. Wen, Y. Mao, and Y. Shi, “RIS-Assisted Federated Learning in Multi-Cell Wireless Networks,” ZTE Commun., vol. 21, no. 1, pp. 25-37, Mar. 2022, doi: 10.12142/ZTECOM.202301004.
  12. J. Ren, Y. He, D. Wen, G. Yu, K. Huang, and D. Guo, “Scheduling in Cellular Federated Edge Learning with Importance and Channel Awareness,” IEEE Trans. Wireless Commun., vol. 19, no. 11, pp. 7690-7703, Nov. 2020, doi: 10.1109/TWC.2020.3015671.

Other Topics

  1. D. Wen, G. Zhu, and K. Huang, “Reduced-Dimension Design of MIMO Over-the-Air Computing for Data Aggregation in Clustered IoT Networks,” IEEE Trans. Wireless Commun., vol. 18, no. 11, pp. 5255-5268, Nov. 2019, doi: 10.1109/TWC.2019.2934956.
  2. D. Wen, G. Yu, R. Li, Y. Chen, and G.Y. Li, “Results on Energy-and Spectral-Efficiency Tradeoff in Cellular Networks with Full-Duplex Enabled Base Stations,” IEEE Trans. Wireless Commun., vol. 16, no. 3, pp. 1494-1507, Mar. 2017, doi: 10.1109/TWC.2016.2647593.
  3. D. Wen, G. Yu, “Full-Duplex and Half-Duplex: Power Efficiency Comparison,” Electron. Lett., vol. 52, no. 6, pp. 483-485, Mar. 2016.
  4. D. Wen and G. Yu, “Time-Division Cellular Networks with Full-Duplex Base Stations,” IEEE Commun. Lett., vol. 20, no. 2, pp. 392-395, Feb. 2016, doi: 10.1109/LCOMM.2015.2512865.
  5. G. Yu, D. Wen, and F. Qu, “Joint User Scheduling and Channel Allocation for Cellular Networks with Full Duplex Base Stations,” IET Commun., vol. 1, no. 5, pp. 479-486, Mar. 2016.
  6. H. Zhu, L. Chen, D. Wen, X. Chen, and W. Wang, “Balancing Straggler Mitigation and Information Protection for Matrix Multiplication in Heterogeneous Multi-Group Networks,” in IEEE Trans. Commun., doi: 10.1109/TCOMM.2024.3450797.
  7. L. Chen, D. Wen, C. Zhong, G. Yu, “Hybrid Full-/Half-Duplex Cellular Networks: User Admission and Power Control,” Front. Inf. Technol. Electron. Eng., vol. 19, no. 3, pp. 379-387, May 2018.

Conference Papers

  1. D. Wen et al., “Over-the-Air Federated Edge Learning with Integrated Sensing, Communication, and Computation,” 2024 IEEE/CIC International Conference on Communications in China (ICCC), Hangzhou, China, 2024, pp. 862-867.
  2. Z. Zhou, S. Huang, Y. Wu, D. Wen, T. Wang, H. Cai, and Y. Shi, “Communication-efficient Federated Learning with Privacy Enhancing via Probabilistic Scheduling,” 2024 IEEE/CIC International Conference on Communications in China (ICCC), Hangzhou, China, 2024, pp. 1233-1238.
  3. S. Lin, X. Xu, Q. Chen, Z. Zhang, D. Wen, G. Tao, and H. Jiang, “End-to-End Hybrid Beamforming for mmWave Integrated Access and Backhaul with Active Sensing Strategy,” 2024 IEEE Wireless Communications and Networking Conference (WCNC), Dubai, United Arab Emirates, 2024, pp. 1-6.
  4. Z. Yang, Z. Yu, X. Liu, D. Wen, Y. Zhou, and Y. Shi, “Latency-Aware Microservice Deployment for Edge AI Enabled Video Analytics,” 2024 IEEE Wireless Communications and Networking Conference (WCNC), Dubai, United Arab Emirates, 2024.
  5. J. Yang, Y. Mao, D. Wen, Y. Zhou and Y. Shi, “RIS-Assisted Multi-Device Edge AI Inference,” 2024 IEEE Wireless Communications and Networking Conference (WCNC), Dubai, United Arab Emirates, 2024.
  6. C. Liu, S. Liu, D. Wen and G. Yu, “Adaptive Cluster Head Selection and Spectrum Allocation for D2D-Enabled Collaborative Learning,” 2023 IEEE Globecom Workshops (GC Wkshps), Kuala Lumpur, Malaysia, 2023, pp. 491-496.
  7. D. Wang, D. Wen, Y. He and G. Yu, “Device Scheduling for Privacy-Aware Integrated Sensing, Computation, and Communication Systems,” 2023 IEEE Globecom Workshops (GC Wkshps), Kuala Lumpur, Malaysia, 2023, pp. 957-962.
  8. Y. Wang, J. Zhu, Y. Mao, D. Wen, X. Tian and Y. Shi, “Hierarchical Federated Edge Learning over Space-Air-Ground Integrated Networks,” 2023 IEEE Globecom Workshops (GC Wkshps), Kuala Lumpur, Malaysia, 2023, pp. 190-196.
  9. Z. Zhuang, D. Wen, and Y. Shi, “Decentralized Over-the-Air Computation for Edge AI Inference with Integrated Sensing and Communication,” 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia, 2023, pp. 4644-4649.
  10. S. Lin, M. Lee, Q. Chen, D. Wen, W. Du, Z. He, “OverGNN Assisted Power Allocation for Heterogeneous Ultra-Dense Networks,” 2023 International Conference on Wireless Communications and Signal Processing (WCSP), Hangzhou, China, 2023, pp. 152-157.
  11. X. Ye, Y. Sun, D. Wen, G. Pan and S. Zhang, “End-to-End Delay Minimization based on Joint Optimization of DNN Partitioning and Resource Allocation for Cooperative Edge Inference,” 2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall), Hong Kong, Hong Kong, 2023, pp. 1-7.
  12. P. Yang, D. Wen, Q. Zeng, T. Wang, and Y. Shi, “Communication-Efficient Vertically Split Inference via Over-the-Air Computation,” 2023 IEEE 24th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Shanghai, China, 2023, pp. 1-5.
  13. D. Wen, P. Liu, G. Zhu, Y. Shi, J. Xu, Y. C. Eldar, and S. Cui, “Task-Oriented Sensing, Computation, and Communication Integration for Multi-Device Edge AI,” in Proc. IEEE ICC 2023, Rome, Italy, 2023, pp. 3608-3613.
  14. D. Wen, X. Jiao, P. Liu, G. Zhu, Y. Shi, and K. Huang, “Task-Oriented Over-the-Air Computation for Multi-Device Edge Split Inference,” 2023 IEEE Wireless Communications and Networking Conference (WCNC), Glasgow, United Kingdom, 2023, pp. 1-6.
  15. L. Zeng, D. Wen, G. Zhu, C. You, Q. Chen and Y. Shi, “Joint Bandwidth Allocation, Computation Control, and Device Scheduling for Federated Learning with Energy Harvesting Devices,” 2022 56th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2022, pp. 1164-1168.
  16. Y. Wang, C. Zou, D. Wen, and Y. Shi, “Federated Learning over LEO Satellite,” 2022 IEEE Globecom Workshops (GC Wkshps), Rio de Janeiro, Brazil, 2022, pp. 1652-1657.
  17. D. Wen, M. Bennis, K. Huang, “Accelerating Partitioned Edge Learning via Joint Parameter-and-Bandwidth Allocation,” in Proc. IEEE Globecom 2020, Dec. 2020.
  18. J. Ren, Y. He, D. Wen, G. Yu, K. Huang, and D. Guo, “Importance- and Channel-Aware Scheduling in Cellular Federated Edge Learning”, in 54th Asilomar Conference on Signals, Systems and Computers, Nov. 2020.
  19. D. Wen, G. Zhu, and K. Huang, “Reduced-Dimension Design of MIMO AirComp for Data Aggregation in Clustered IoT Networks,” in Proc. IEEE Globecom 2019, Dec. 2019.
  20. D. Wen, G. Yu, R. Li, Y. Chen, and G. Y. Li, “Energy- and Spectral-Efficiency Tradeoff in Full-Duplex Enabled Cellular Networks,” in Proc. IEEE Globecom Workshops 2016, Dec. 2016.
  21. Z. Zhang, G. Yu, D. Wen, R. Liu, “Joint User Pairing, Resource Block Allocation, and Power Control for Full-Duplex Cellular Networks”, in IEEE/CIC International Conference on Communications in China (ICCC), Jul. 2016.
  22. D. Wen, G. Yu, and L. Xu, “Energy-Efficient Mode Selection and Power Control for Device-to-Device Communications,” in Proc. IEEE WCNC 2016, Apr. 2016.