Yong Zhou
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Books

  1. Y. Zhou, Y. Zou, Y. Wu, Y. Shi, and J. Zhang, Machine Learning for Low Latency Communications, Elsevier, 2024. (ISBN: 978-0-443-22073-9)

  2. Y. Shi, K. Yang, Z. Yang, and Y. Zhou, Mobile Edge Artificial Intelligence: Opportunities and Challenges, Elsevier, 2021. (ISBN: 978-0-12-823817-2)

Journal Articles

  1. M. Tao, Y. Zhou, Y. Shi, J. Lu, S. Cui, J. Lu, and K. Letaief, “Federated Edge Learning for 6G: Foundations, Architectures, and Applications,” Proceedings of the IEEE, to appear.

  2. F. Zhou, Z. Wang, H. Shan, L. Wu, X. Tian, Y. Shi, and Y. Zhou, “Over-the-Air Hierarchical Personalized Federated Learning,” IEEE Trans. Veh. Technol., to appear.

  3. J. Huang, L. Lian, D. Wen, Y. Zhou, F. Wang, W. Wang, and Y. Shi, “Dynamic UAV-Assisted Cooperative Edge AI Inference,” IEEE Trans. Wireless Commun., to appear.

  4. P. Yang, D. Wen, Q. Zeng, Y. Zhou, T. Wang, H. Cai, and Y. Shi, “Over-the-Air Computation Empowered Vertically Split Inference,” IEEE Trans. Wireless Commun., to appear.

  5. Z. Wang, Y. Zhou, and Y. Shi, “Decentralized Over-the-Air Federated Learning in Full-Duplex MIMO Networks,” IEEE Trans. Wireless Commun., to appear.

  6. Z. Wang, Y. Zhou, and Y. Shi, “Over-the-Air Federated Graph Learning,” IEEE Trans. Wireless Commun., to appear.

  7. Z. Wang, M. Bennis, and Y. Zhou, “Graph Attention-based MADRL for Access Control and Resource Allocation in Wireless Networked Control Systems,” IEEE Trans. Wireless Commun., to appear.

  8. D. Wen, X. Li, Y. Zhou, Y. Shi, S. Wu, and C. Jiang, “Integrated Sensing-Communication-Computation for Edge Artificial Intelligence,” IEEE Internet Things Mag., to appear.

  9. L. Wu, P. Sun, H. Chen, Y. Zuo, Y. Zhou, and Y. Yang, “NOMA-Enabled Multiuser Offloading in Multicell Edge Computing Networks: A Coalition Game Based Approach,” IEEE Trans. Netw. Sci. Eng., to appear.

  10. Y. Shi, L. Zeng, J. Zhu, Y. Zhou, C. Jiang, and K. Letaief, “Satellite Federated Edge Learning: Architecture Design and Convergence Analysis,” IEEE Trans. Wireless Commun., vol. 23, no. 10, pp. 15212-15229, Oct. 2024.

  11. Y. Zou, Y. Zhou, X. Chen, and Y. Eldar, “Proximal Gradient-Based Unfolding for Massive Random Access in IoT Networks,” IEEE Trans. Wireless Commun., vol. 23, no. 10, pp. 14530-14545, Oct. 2024.

  12. S. Xia, Y. Shi, Y. Zhou, Y. Wu, L. Yang, and K. Letaief, “Federated Learning with Massive Random Access,” IEEE Trans. Wireless Commun., vol. 23, no. 10, pp. 13856-13871, Oct. 2024.

  13. S. Wan, Z. Wang, and Y. Zhou, “Scalable Hybrid Beamforming for Multi-User MISO Systems: A Graph Neural Network Approach,” IEEE Trans. Wireless Commun., vol. 23, no. 10, pp. 13694-13706, Oct. 2024.

  14. D. Wang, H. Zhu, C. Qiu, Y. Zhou, and J. Lu, “Distributed Task Offloading in Cooperative Mobile Edge Computing Networks,” IEEE Trans. Veh. Technol., vol. 73, no. 7, pp. 10487-10501, Jul. 2024.

  15. Q. An, Y. Zhou, Z. Wang, H. Shan, Y. Shi, and M. Bennis, “Online Optimization for Over-the-Air Federated Learning with Energy Harvesting,” IEEE Trans. Wireless Commun., vol. 23, no. 7, pp. 7291-7306, Jul. 2024.

  16. Z. Wang, Y. Zhao, Y. Zhou, Y. Shi, C. Jiang, and K. Letaief, “Over-the-Air Computation: Foundations, Technologies, and Applications,” IEEE Internet Things J., vol. 11, no. 14, pp. 24634-24658, Jul. 2024.

  17. J. Zhu, Y. Shi, Y. Zhou, C. Jiang, W. Chen, and K. Letaief, “Over-the-Air Federated Learning and Optimization,” IEEE Internet Things J., vol. 11, no. 10, pp. 16996-17020, May 2024.

  18. M. Fu, Y. Shi, and Y. Zhou, “Federated Learning via Unmanned Aerial Vehicle,” IEEE Trans. Wireless Commun., vol. 23, no. 4, pp. 2884-2900, Apr. 2024.

  19. Y. Shi, S. Xia, Y. Zhou, Y. Mao, C. Jiang, and M. Tao, “Vertical Federated Learning over Cloud-RAN: Convergence Analysis and System Optimization,” IEEE Trans. Wireless Commun., vol. 23, no. 2, pp. 1327-1342, Feb. 2024.

  20. J. Zhu, M. Fu, Y. Shi, Y. Zhou, Y. Wu, and L. Fu, “Latency Minimization for Wireless Federated Learning with Heterogeneous Local Model Updates,” IEEE Internet Things J., vol. 11, no. 1, pp. 444-461, Jan. 2024.

  21. Y. Zhou, Y. Shi, H. Zhou, J. Wang, L. Fu, and Y. Yang “Towards Scalable Wireless Federated Learning: Challenges and Solutions,” IEEE Internet Things Mag., vol. 6, no. 4, pp. 10-16, Dec. 2023.

  22. L. Qiao and Y. Zhou, “Timely Edge Inference in Wireless Networks: An Accuracy-Freshness Tradeoff,” IEEE Trans. Veh. Technol., vol. 72, no. 12, pp. 16817- 16822, Dec. 2023.

  23. Y. Shi, L. Lian, Y. Shi, Z. Wang, Y. Zhou, L. Fu, L. Bai, J. Zhang, and W. Zhang, “Machine Learning for Large-Scale Optimization in 6G Wireless Networks,” IEEE Commun. Sur. Tut., vol. 25, no. 4, pp. 2088-2132, Fourth Quarter, 2023.

  24. Y. Yang, M. Ma, H. Wu, Q. Yu, P. Zhang, X. You, et al., Y. Zhou, et al., “6G Network AI Architecture for Everyone-Centric Customized Services,” IEEE Netw., vol. 37, no. 5, pp. 71-80, Sept. 2023.

  25. Z. Wang, Y. Zhou, Y. Zou, Q. An, Y. Shi, and M. Bennis, “A Graph Neural Network Learning Approach to Optimize RIS-Assisted Federated Learning,” IEEE Trans. Wireless Commun., vol. 22, no. 9, pp. 6092–6106, Sep. 2023.

  26. J. He, Y. Mao, Y. Zhou, T. Wang, and Y. Shi, “Reconfigurable Intelligent Surfaces Empowered Green Wireless Networks with User Admission Control,” IEEE Trans. Commun., vol. 71, no. 7, pp. 4062-4078, Jul. 2023.

  27. M. Fu, Y. Zhou, Y. Shi, C. Jiang, and W. Zhang, “UAV-Assisted Multi-Cluster Over-the-Air Computation,” IEEE Trans. Wireless Commun., vol. 22, no. 7, pp. 4668-4682, Jul. 2023.

  28. Y. Shi, Y. Zhou, D. Wen, Y. Wu, C. Jiang, and, K. Letaief, “Task-Oriented Communications for 6G: Vision, Principles, and Technologies,” IEEE Wireless Commun. Mag., vol. 30, no. 3, pp. 78-85, Jun. 2023.

  29. H. Zhu, Y. Zhou, H. Qian, Y. Shi, X. Chen, and Y. Yang, “Online Client Selection for Asynchronous Federated Learning with Fairness Consideration,” IEEE Trans. Wireless Commun., vol. 22, no. 4, pp. 2493-2506, Apr. 2023.

  30. Z. Yang, Y. Shi, Y. Zhou, Z. Wang, and K. Yang, “Trustworthy Federated Learning via Blockchain,” IEEE Internet Things J., vol. 10, no. 1, pp. 92-109, Jan. 2023.

  31. Y. Zou, Z. Wang, X. Chen, H. Zhou, and Y. Zhou, “Knowledge-Guided Learning for Transceiver Design in Over-the-Air Federated Learning,” IEEE Trans. Wireless Commun., vol. 22, no. 1, pp. 270-285, Jan. 2023.

  32. P. Yang, Y. Jiang, T. Wang, Y. Zhou, Y. Shi, and C. Jones, “Over-the-Air Federated Learning via Second-Order Optimization,” IEEE Trans. Wireless Commun., vol. 21, no. 21, pp. 10560-10575, Dec. 2022.

  33. W. Fang, Z. Yu, Y. Jiang, Y. Shi, C. Jones, and Y. Zhou, “Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learning,” IEEE Trans. Signal Process., vol. 70, pp. 5058-5073, Oct. 2022.

  34. Y. Yang, Y. Zhou, Y. Wu, and Y. Shi, “Differentially Private Federated Learning via Reconfigurable Intelligent Surface,” IEEE Internet Things J., vol. 9, no. 20, pp. 19728-19743, Oct. 2022.

  35. Z. Wang, Y. Zhou, Y. Shi, and W. Zhuang, “Interference Management for Over-the-Air Federated Learning in Multi-Cell Wireless Networks,” IEEE J. Sel. Areas Commun., vol. 40. no. 8, pp. 2361-2377, Aug. 2022.

  36. H. Zhu, Y. Zhou, X. Luo, and H. Zhou, “Joint Control of Power, Beamwidth, and Spacing for Platoon-based Vehicular Cyber-Physical Systems,” IEEE Trans. Veh. Technol., vol. 71, no. 8, pp. 8615-8629, Aug. 2022.

  37. J. He, K. Yu, Y. Shi, Y. Zhou, W. Chen, and K. Letaief, “Reconfigurable Intelligent Surface Assisted Massive MIMO with Antenna Selection,“ IEEE Trans. Wireless Commun., vol. 21, no. 7, pp. 4769-4783, Jul. 2022.

  38. M. Fu, Y. Zhou, Y. Shi, W. Chen, and R. Zhang, “UAV-Assisted Over-the-Air Computation,“ IEEE Trans. Wireless Commun., vol. 21, no. 7, pp. 4909-4924, Jul. 2022.

  39. K. Wang, Y. Zhou, Q. Wu, W. Chen, and Y. Yang, “Task Offloading in Hybrid Intelligent Reflecting Surface and Massive MIMO Relay Networks,” IEEE Trans. Wireless Commun., vol. 21, no. 6, pp. 1536-1276, Jun. 2022.

  40. M. Fu, T. Jiang, H. Choi, Y. Zhou, and Y. Shi, “Sparse and Low-Rank Optimization for Pliable Index Coding via Alternating Projection,” IEEE Trans. Commun., vol. 70, no. 6, pp. 3708-3724, Jun. 2022.

  41. L. Hu, Z. Wang, H. Zhu, and Y. Zhou, “RIS-Assisted Over-the-Air Federated Learning in Millimeter Wave MIMO Networks,” J. Commun. Inf. Netw., vol. 7, no. 2, pp. 145-156, Jun. 2022.

  42. Z. Wang, J. Zong, Y. Zhou, Y. Shi, and V. W.S. Wong, “Decentralized Multi-Agent Power Control in Wireless Networks with Frequency Reuse,” IEEE Trans. Commun., vol. 70, no. 3, pp. 1666-1681, Mar. 2022.

  43. Y. Zhou and S. Sun, “Performance Analysis of Opportunistic Beam Splitting NOMA in Millimeter Wave Networks,” IEEE Trans. Veh. Technol., vol. 71, no. 3, pp. 3030-3043, Mar. 2022.

  44. M. Yang, H. Qian, X. Wang, Y. Zhou and H. Zhu, “Client Selection for Federated Learning with Label Noise," IEEE Trans. Veh. Technol., vol. 71, no. 2, pp. 2193-2197, Feb. 2022.

  45. Z. Wang, H. Zhu, M. He, Y. Zhou, X. Luo, and N. Zhang, “GAN and Multi-Agent DRL based Decentralized Traffic Light Signal Control,” IEEE Trans. Veh. Technol., vol. 71, no. 2, pp. 1333-1348, Feb. 2022.

  46. Y. Shi, H. Choi, Y. Shi, and Y. Zhou, “Algorithm Unrolling for Massive Access via Deep Neural Networks with Theoretical Guarantee,” IEEE Trans. Wireless Commun., vol. 21, no. 2, pp. 945-959, Feb. 2022.

  47. Z. Wang, J. Qiu, Y. Zhou, Y. Shi, L. Fu, W. Chen, and K. Letaief, “Federated Learning via Intelligent Reflecting Surface,” IEEE Trans. Wireless Commun., vol. 21, no. 2, pp. 808-822, Feb. 2022.

  48. W. Fang, Y. Jiang, Y. Shi, Y. Zhou, W. Chen, and K. Letaief, “Over-the-Air Computation via Reconfigurable Intelligent Surface,”IEEE Trans. Commun., vol. 69, no. 12, pp. 8612-8626, Dec. 2021.

  49. S. Xia, Y. Shi, Y. Zhou, and X. Yuan, “Reconfigurable Intelligent Surfaces for Massive Connectivity: Joint Activity Detection and Channel Estimation,” IEEE Trans. Signal Process., vol. 69, pp. 5693-5707, Oct. 2021.

  50. H. Zhu, Z. Wang, F. Yang, Y. Zhou, and X. Luo, “Intelligent Traffic Network Control in the Era of Internet of Vehicles,” IEEE Trans. Veh. Technol., vol. 70. no. 10, pp. 9787-9802, Oct. 2021.

  51. B. Li, Q. Wang, H. Chen, Y. Zhou, and Y. Li, “Optimizing Information Freshness for Cooperative IoT Systems with Stochastic Arrivals,” IEEE Internet Things J., vol. 8, no. 19, pp. 14485-14500, Oct. 2021.

  52. M. Fu, Y. Zhou, Y. Shi, and K. Letaief, "Reconfigurable Intelligent Surface Empowered Downlink Non-Orthogonal Multiple Access,” IEEE Trans. Commun., vol. 69, no. 6, pp. 3802-3817, Jun. 2021.

  53. S. Hua, Y. Zhou, K. Yang, Y. Shi, and K. Wang, “Reconfigurable Intelligent Surface for Green Edge Inference,” IEEE Trans. Green Commun. Netw., vol. 5, no. 2, pp. 964-979, Jun. 2021.

  54. H. Choi, T. Jiang, Y. Shi, X. Liu, Y. Zhou, and K. Letaief, “Large-Scale Beamforming for Massive MIMO via Randomized Sketching,” IEEE Trans. Veh. Technol., vol. 70, no. 5, pp. 4669-4681, May 2021.

  55. K. Wang, Y. Zhou, J. Li, L. Shi, W. Chen, and L. Hanzo, “Energy-Efficient Task Offloading in Massive MIMO-Aided Multi-Pair Fog Computing Networks,” IEEE Trans. Commun., vol. 69, no. 4, pp. 2123-2137, Apr. 2021.

  56. A. Mostafa, V. W.S. Wong, Y. Zhou, R. Schober, Z. Luo, S. Liao, and M. Ding, “Aggregate Preamble Sequence Design and Detection for Massive IoT with Deep Learning,” IEEE Trans. Veh. Technol., vol. 70, no. 4, pp. 3800-3816, Apr. 2021.

  57. P. Cai, J. Zong, X. Luo, Y. Zhou, S. Chen, and H. Qian, “Downlink Channel Tracking for Intelligent Reflecting Surface-Aided FDD MIMO Systems," IEEE Trans. Veh. Technol., vol. 70, no. 4, pp. 3800-3816, Apr. 2021.

  58. Z. Wang, Y. Shi, Y. Zhou, H. Zhou, and N. Zhang, “Wireless-Powered Over-the-Air Computation in Intelligent Reflecting Surface Aided IoT Networks,” IEEE Internet Things J., vol. 8, no. 3, pp. 1585-1598, Feb. 2021.

  59. J. Zhang, J. Zhang, Y. Zhou, H. Ji, J. Sun, and N. Al-Dhahir, “Energy and Spectral Efficiency Tradeoff via Rate Splitting and Common Beamforming Coordination in Multicell Networks,” IEEE Trans. Commun., vol. 68, no. 12, pp. 7719-7731, Dec. 2020.

  60. K. Yang, Y. Shi, Y. Zhou, Z. Yang, L. Fu, and W. Chen, “Federated Machine Learning for Intelligent IoT via Reconfigurable Intelligent Surface,” IEEE Netw., vol. 34, no. 5, pp. 16-22, Sep. 2020.

  61. J. Li, Y. Zhou, and H. Chen, “On the Age of Information for Multicast Transmission with Fixed and Random Deadlines in IoT Systems,” IEEE Internet Things J., vol. 7, no. 9, pp. 8178-8191, Sep. 2020.

  62. K. Yang, Y. Zhou, Z. Yang, and Y. Shi, “Communication-Efficient Edge AI Inference over Wireless Networks,” ZTE Commun., vol. 18, no. 2, pp. 31-39, Jun. 2020.

  63. K. Wang, Y. Zhou, Z. Liu, Z. Shao, X. Luo, and Y. Yang, “Online Task Scheduling and Resource Allocation for Intelligent NOMA-based Industrial Internet of Things,” IEEE J. Sel. Areas Commun., vol. 38, no. 5, pp. 803-815, May 2020.

  64. A. Mostafa, Y. Zhou, and V. W.S. Wong, “Connection Density Maximization of Narrowband IoT Systems with NOMA,” IEEE Trans. Wireless Commun., vol. 18, no. 10, pp. 4708-4722, Oct. 2019.

  65. Y. Zhou, J. Li, Y. Shi, and V. W.S. Wong, “Flexible Functional Split Design for Downlink C-RAN with Capacity-Constrained Fronthaul,” IEEE Trans. Veh. Technol., vol. 68, no. 6, pp. 6050-6063, Jun. 2019.

  66. Y. Gu, H. Chen, Y. Zhou, Y. Li, and B. Vucetic, “Timely Status Update in Internet of Things Monitoring Systems: An Age-Energy Tradeoff,” IEEE Internet Things J., vol. 6, no. 3, pp. 5324-5335, Jun. 2019.

  67. Y. Zhou, V. W.S. Wong, and R. Schober, “Coverage and Rate Analysis of Millimeter Wave NOMA Networks with Beam Misalignment,” IEEE Trans. Wireless Commun., vol. 17, no. 12, pp. 8211-8227, Dec. 2018.

  68. L. Xu, Y. Zhou, P. Wang, and W. Liu, “Max-Min Resource Allocation for Video Transmission in NOMA-based Cognitive Wireless Networks,” IEEE Trans. Commun., vol. 66, no. 11, pp. 5804-5813, Nov. 2018.

  69. Y. Zhou, V. W.S. Wong, and R. Schober, “Stable Throughput Regions of Opportunistic and Cooperative NOMA with Full-Duplex Relaying,” IEEE Trans. Wireless Commun., vol. 17, no. 8, pp. 5059-5075, Aug. 2018.

  70. Y. Zhou, V. W.S. Wong, and R. Schober, “Dynamic Decode-and-Forward based Cooperative NOMA with Spatially Random Users,” IEEE Trans. Wireless Commun., vol. 17, no. 5, pp. 3340-3356, May 2018.

  71. Y. Zhou and W. Zhuang, “Opportunistic Cooperation in Wireless Ad Hoc Networks with Interference Correlation,” Peer Peer Netw. Appl., vol. 10, no. 1, pp. 238-252, Jan. 2017.

  72. B. Niu, Y. Zhou, H. Shah-Mansouri, and V. W.S. Wong, “A Dynamic Resource Sharing Mechanism for Cloud Radio Access Networks,” IEEE Trans. Wireless Commun., vol. 15, no. 12, pp. 8325-8338, Dec. 2016.

  73. Y. Zhou and W. Zhuang, “Performance Analysis of Cooperative Communication in Decentralized Wireless Networks with Unsaturated Traffic,” IEEE Trans. Wireless Commun., vol. 15, no. 5, pp. 3518-3530, May, 2016.

  74. Y. Zhou and W. Zhuang, “Throughput Analysis of Cooperative Communication in Wireless Ad Hoc Networks with Frequency Reuse,” IEEE Trans. Wireless Commun., vol. 14, no. 1, pp. 205-218, Jan. 2015.

  75. W. Zhuang and Y. Zhou, “A Survey of Cooperative MAC Protocols for Mobile Communication Networks,” J. Internet Technol., vol. 14, no. 4, pp. 541-559, Jul. 2013. (Invited paper)

  76. Y. Zhou, J. Liu, L. Zheng, C. Zhai, and H. Chen, “Link-Utility-based Cooperative MAC Protocol for Wireless Multi-Hop Networks,” IEEE Trans. Wireless Commun., vol. 10, no. 3, pp. 995-1005, Mar. 2011.

  77. H. Chen, J. Liu, Z. Dong, Y. Zhou, and W. Guo, “Exact Capacity Analysis of Partial Relay Selection under Outdated CSI over Rayleigh Fading Channels,” IEEE Trans. Veh. Technol., vol. 60, no. 8, pp. 4014-4018, Oct. 2011.

  78. C. Zhai, H. Xu, J. Liu, L. Zheng, and Y. Zhou, “Performance of Opportunistic Relaying with Truncated ARQ over Nakagami-m Fading Channels,” Trans. Emerging Telecommun. Technol., vol. 23, no. 1, pp. 50-66, Sept. 2011.

  79. L. Zheng, J. Liu, C. Zhai, H. Chen, and Y. Zhou, “Energy Efficient Cooperative Routing Algorithm with Truncated Automatic Repeat Request over Nakagami-m Fading Channels,” IET Commun., vol. 5, no. 8, Jun. 2011.

  80. Y. Zhou, J. Liu, C. Zhai, and L. Zheng, “Two-Transmitter Two-Receiver Cooperative MAC Protocol: Cross-Layer Design and Performance Analysis,” IEEE Trans. Veh. Technol., vol. 59, no. 8, pp. 4116-4127, Oct. 2010.

  81. H. Chen, J. Liu, L. Zheng, C. Zhai, and Y. Zhou, “Approximate SEP Analysis for DF Cooperative Networks with Opportunistic Relaying,” IEEE Signal Process. Lett., vol. 17, no. 9, pp. 779-782, Sept. 2010.

  82. H. Chen, J. Liu, L. Zheng, C. Zhai, and Y. Zhou, “An Improved Selection Cooperation Scheme for Decode-and-Forward Relaying,” IEEE Commun. Lett., vol. 14, no. 12. pp. 1143-1145, Dec. 2010.

Conference Papers

  1. Z. Wang, Y. Zhou, Y. Shi, and K. Letaief, “Federated Low-Rank Adaptation for Large Language Model Fine-Tuning Over Wireless Networks,” in Proc. IEEE Globecom, Cape Town, South Africa, Dec. 2024.

  2. Y. Zhu, P. Yang, J. Zhu, D. Wen, T. Wang, Y. Zhou, Y. Shi, and C. Jiang, “Satellite Federated Fine-Tuning for Foundation Models: Architecture Design and System Optimization,” in Proc. IEEE Globecom, Cape Town, South Africa, Dec. 2024.

  3. S. Wan, X. Bian, W. Wang, T. Hou, and Y. Zhou, “Robust Decentralized Coordinated Precoding in Multi-cell Coherent Joint Transmission Networks,” in Proc. IEEE Globecom, Cape Town, South Africa, Dec. 2024.

  4. J. You, Y. Wu, D. Wen, Y. Zhou, Y. Jiang, and Y. Shi, “Dynamic Communication in Multi-Agent Reinforcement Learning via Information Bottleneck,” in Proc. IEEE Globecom, Cape Town, South Africa, Dec. 2024.

  5. Z. Yu, H. Cheng, Z. Yang, X. Liu, Y. Jiang, Y. Zhou, and Y. Shi, “Microservice Deployment for Satellite Edge AI Inference via Deep Reinforcement Learning,” in Proc. IEEE PIMRC, Valencia, Spain, Sep. 2024.

  6. W. Meng, Z. Dong, Y. Zhou, L. Li, and Z. Liu, “RIS-Aided User Localization Design with Multiple Signal Classification based Orthogonal Subspace Projection,” in Proc. IEEE VTC, Singapore, Jun. 2024.

  7. F. Zhou, Z. Wang, Y. Shi, and Y. Zhou, “Decentralized Satellite Federated Learning via Intra- and Inter-Orbit Communications,” in Proc. IEEE ICC Workshop, Denver, CO, Jun. 2024.

  8. G. Gao, Q. An, Z. Wang, Z. Wang, Y. Shi, and Y. Zhou, “Over-the-Air Computation Assisted Federated Learning With Progressive Training,” in Proc. IEEE ICC, Denver, CO, Jun. 2024.

  9. M. Wu, Z. Dong, Z. Wang, Q. An, Y. Shi, and Y. Zhou, “Delay Minimization for NOMA-Assisted Federated Learning,” in Proc. IEEE WCNC, Dubai, UAE, Apr. 2024.

  10. J. Yang, Y. Mao, D. Wen, Y. Zhou, and Y. Shi, “RIS-Assisted Multi-Device Edge AI Inference,” in Proc. IEEE WCNC, Dubai, UAE, Apr. 2024.

  11. Z. Yang, Z. Yu, X. Liu, D. Wen, Y. Zhou, and Y. Shi, “Latency-Aware Microservice Deployment for Edge AI Enabled Video Analytics,” in Proc. IEEE WCNC, Dubai, UAE, Apr. 2024.

  12. F. Zhou, X. Chen, H. Shan, and Y. Zhou, “Adaptive Transceiver Design for Wireless Hierarchical Federated Learning,” in Proc. IEEE VTC, Hong Kong, Oct. 2023.

  13. Y. Pan, Z. Wang, L. Wu, and Y. Zhou, “IRS-Assisted Digital Over-the-Air Federated Learning,” in Proc. IEEE Globecom, Kuala Lumpur, Malaysia, Dec. 2023.

  14. Z. Li, Z. Wang, Z. Wang, and Y. Zhou, “Energy-Efficient Federated Learning Over Hierarchical Aerial Wireless Networks,” in Proc. IEEE PIMRC, Toronto, Canada, Sept. 2023.

  15. J. Jin, Z. Wang, L. Wu, and Y. Zhou, “Hybrid Reconfigurable Intelligent Surface Assisted Over-the-Air Federated Learning,” in Proc. IEEE ICC Workshop, Rome, Italy, May 2023.

  16. Y. Zhao, Z. Wang, Z. Wang, X. Chen, and Y. Zhou, “Learning to Beamform for Dual-Functional MIMO Radar-Communication Systems,” in Proc. IEEE ICC, Rome, Italy, May 2023.

  17. F. Zhou, Z. Wang, X. Luo, and Y. Zhou, “Over-the-Air Computation Assisted Hierarchical Personalized Federated Learning,” in Proc. IEEE ICC, Rome, Italy, May 2023.

  18. N. Lee, H. Shan, M. Song, Y. Zhou, Z. Zhao, X. Li, and Z. Zhang, “Decentralized Federated Learning Under Communication Delays,” in Proc. IEEE SECON Workshops, Virtual Conference, Sept. 2022.

  19. L. Qiao and Y. Zhou, “Timely Status Update for Wireless Data Aggregation via Over-the-Air Computation,” in Proc. IEEE Globecom, Rio de Janeiro, Brazil, Dec. 2022.

  20. C. Gong, M. Ma, L. Wu, W. Liu, Y. Zhou, and Y. Yang, “Task Offloading and Resource Allocation in CPU-GPU Heterogeneous Networks,” in Proc. IEEE Globecom, Rio de Janeiro, Brazil, Dec. 2022.

  21. J. Guo, K. Li, H. Li, W. Liu, Z. Zhuang, Y. Zhou, and Y. Yang, “Markov State Transition Modeling in Complex High-Dimensional State Space Based on Fuzzy Integral,”in Proc. IEEE Globecom Workshop, Rio de Janeiro, Brazil, Dec. 2022.

  22. H. Li, K. Li, J. Guo, Y. Yang, and Y. Zhou, “NPSR: Neural Network enabled Phase-Space Reconstruction for Wireless Channel Prediction,” in Proc. IEEE Globecom Workshop, Rio de Janeiro, Brazil, Dec. 2022.

  23. H. Zhu, M. Yang, J. Kuang, H. Qian, and Y. Zhou, “Client Selection for Asynchronous Federated Learning with Fairness Consideration,” in Proc. IEEE ICC Workshop, Seoul, South Korea, May 2022.

  24. L. Hu, Z. Wang, H. Zhu, Y. Shi, and Y. Zhou, “RIS-Assisted Over-the-Air Computation in Millimeter Wave Communication Networks,” in Proc. IEEE VTC Spring, Helsinki, Finland, 2022.

  25. S. Liang, Y. Zou, and Y. Zhou, “GAN-Based Joint Activity Detection and Channel Estimation for Grant-Free Random Access,” in Proc. IEEE ICASSP, Singapore, May 2022.

  26. Y. Zou, Y. Zhou, Y. Shi, and X. Chen, "Learning Proximal Operator Methods for Massive Connectivity in IoT Networks,” in Proc. IEEE Globecom, Virtual Conferences, Dec. 2021.

  27. K. Wang, Y. Zhou, Q. Wu, W. Chen, and Y. Yang, "Multi-Tier Task Offloading with Intelligent Reflecting Surface and Massive MIMO Relay,” in Proc. IEEE Globecom, Virtual Conferences, Dec. 2021.

  28. Y. Shi, M. Fu, Y. Zhou, and Y. Shi, "Capacity Region of Intelligent Reflecting Surface Aided Wireless Networks via Active Learning,” in Proc. IEEE Globecom, Virtual Conferences, Dec. 2021.

  29. J. Li, M. Fu, Y. Zhou, and Y. Shi, “Double-RIS Assisted Over-the-Air Computation,” in Proc. IEEE Globecom Workshop, Virtual Conferences, Dec. 2021.

  30. Y. Du, L. Xing, Y. Zhou, and Y. Shi, “Interference Management for Over-the-Air Computation and Cellular Coexistence Systems,” in Proc. IEEE Globecom Workshop, Virtual Conferences, Dec. 2021.

  31. Z. Yang, Y. Zhou, Y. Wu, and Y. Shi, “Communication-Efficient Quantized SGD for Learning Polynomial Neural Network,” in Proc. IEEE IPCCC Workshop, London UK, Oct. 2021.

  32. W. Fang, Y. Zou, H. Zhu, Y. Shi, and Y. Zhou, “Optimal Receive Beamforming for Over-the-Air Computation,” in Proc. IEEE SPAWC, Virtual Conferences, Sept. 2021.

  33. S. Liang, Y. Shi, and Y. Zhou, “Sparse Signal Processing for Massive Connectivity via Mixed-Integer Programming,” in Proc. IEEE/CIC ICCC, Xiamen, China, Jul. 2021.

  34. J. Zong, F. Yang, Y. Zhou, H. Qian, and X. Luo “Optimal Configuration of Intelligent Walls for Interference Management in Smart Buildings,” in Proc. IEEE/CIC ICCC, Xiamen, China, Jul. 2021.

  35. Y. Shi, Y. Zhou, and Y. Shi, “Over-the-Air Decentralized Federated Learning,” in Proc. IEEE ISIT, Virtual Conference, Jul. 2021.

  36. Y. Yang, Y. Zhou, T. Wang, and Y. Shi, “Reconfigurable Intelligent Surface Assisted Federated Learning with Privacy Guarantee,” in Proc. IEEE ICC Workshop, Virtual Conference, Jun. 2021.

  37. D. Li, K. Wang, H. Zhu, Y. Zhou, and Y. Shi, “Joint Admission Control and Beamforming for Intelligent Reflecting Surface Aided Wireless Networks,” in Proc. IEEE ICC Workshop, Virtual Conference, Jun. 2021.

  38. S. Huang, Y. Zhou, T. Wang, and Y. Shi, “Byzantine-Resilient Federated Machine Learning via Over-the-Air Computation,” in Proc. IEEE ICC Workshop, Virtual Conference, Jun. 2021.

  39. L. Xing, Y. Zhou, and Y. Shi “Over-the-Air Computation via Cloud Radio Access Networks,” in Proc. IEEE ICC Workshop, Virtual Conference, Jun. 2021.

  40. M. Fu, Y. Zhou, and Y. Shi, “Reconfigurable Intelligent Surfaces for Interference Alignment in MIMO Device-to-Device Networks,” in Proc. IEEE ICC Workshop, Virtual Conference, Jun. 2021.

  41. S. Xia, J. Zhu, Y. Yang, Y. Zhou, Y. Shi, and W. Chen, "Fast Convergence Algorithm for Analog Federated Learning,” in Proc. IEEE ICC, Virtual Conference, May 2021.

  42. M. Fu, Y. Zhou, Y. Shi, T. Wang, and W. Chen, "UAV-enabled Over-the-Air Computation,” in Proc. IEEE ICC, Virtual Conference, May 2021.

  43. Z. Wang, H. Zhu, Y. Zhou, and X. Luo, “Joint Traffic Signal and Connected Vehicle Control in IoV via Deep Reinforcement Learning,” in Proc. IEEE WCNC, Nanjing, China, Mar. 2021.

  44. Q. An, Y. Zhou, and Y. Shi, “Robust Design for Reconfigurable Intelligent Surface Assisted Over-the-Air Computation,” in Proc. IEEE WCNC, Nanjing, China, Mar. 2021.

  45. W. Fang, M. Fu, K. Wang, Y. Shi, and Y. Zhou, “Stochastic Beamforming for Reconfigurable Intelligent Surface Aided Over-the-Air Computation,” in Proc. IEEE Globecom, Virtual Conference, Dec. 2020.

  46. J. Li, Y. Zhou, H. Chen, and Y. Shi, “Age of Aggregated Information: Timely Status Update with Over-the-Air Computation,” in Proc. IEEE Globecom, Virtual Conference, Dec. 2020.

  47. B. Li, H. Chen, Y. Zhou, and Y. Li, “Age-Oriented Opportunistic Relaying in Cooperative Status Update Systems with Stochastic Arrivals,” in Proc. IEEE Globecom, Virtual Conference, Dec. 2020.

  48. D. Li, Q. An, Y. Shi, and Y. Zhou, “Multigroup Multicast Transmission via Intelligent Reflecting Surface,” in Proc. IEEE VTC Fall, Virtual Conference, Oct. 2020.

  49. S. Huang, Y. Zhou, and Y. Shi, “Noisy Demixing: Convex Relaxation Meets Nonconvex Optimization,” in Proc. IEEE VTC Fall, Virtual Conference, Oct. 2020.

  50. J. He, K. Yu, Y. Zhou, and Y. Shi, “Reconfigurable Intelligent Surface Enhanced Cognitive Radio Networks,” in Proc. IEEE VTC Fall, Virtual Conference, Oct. 2020.

  51. W. Fang, M. Fu, Y. Shi, and Y. Zhou, “Outage Minimization for Intelligent Reflecting Surface Aided MISO Communication Systems via Stochastic Beamforming,” in Proc. IEEE SAM, Virtual Conference, Jun. 2020.

  52. Y. Shi, S. Xia, Y. Zhou, and Y. Shi, “Sparse Signal Processing for Massive Connectivity via Deep Learning,” in Proc. IEEE ICC, Virtual Conference, Jun. 2020.

  53. Z. Wang, Y. Shi, and Y. Zhou, “Wirelessly Powered Data Aggregation via Intelligent Reflecting Surface Assisted Over-the-Air Computation,” in Proc. IEEE VTC Spring, Virtual Conference, May 2020.

  54. Q. An, Y. Shi, and Y. Zhou, “Reconfigurable Intelligent Surface Assisted Non-Orthogonal Unicast and Broadcast Transmission,” in Proc. IEEE VTC Spring, Virtual Conference, May 2020.

  55. X. Lu, Y. Zhou, and V. W.S. Wong, “A Joint Angle and Distance based User Pairing Strategy for Millimeter Wave NOMA Networks,” in Proc. IEEE WCNC, Virtual Conference, Apr. 2020.

  56. J. Li, Y. Zhou, and H. Chen, “On the Age of Information for Multicast Transmission with Hard Deadlines in IoT Systems,” in Proc. IEEE WCNC, Virtual Conference, Apr. 2020.

  57. S. Sun, M. Fu, Y. Shi, and Y. Zhou, “Towards Reconfigurable Intelligent Surfaces Powered Green Wireless Networks,” in Proc. IEEE WCNC, Virtual Conference, Apr. 2020.

  58. M. Fu, Y. Zhou, and Y. Shi, “Intelligent Reflecting Surface for Downlink Non-Orthogonal Multiple Access Networks,” in Proc. IEEE Globecom, Hawaii, Dec. 2019.

  59. K. Wang, Y. Zhou, Y. Yang, X. Yuan, and X. Luo, “Task Offloading in NOMA-based Fog Computing Networks: A Deep Q-Learning Approach,” in Proc. IEEE Globecom, Hawaii, Dec. 2019.

  60. C. Hsiung, R. Huang, Y. Zhou, and V. W.S. Wong, “Dynamic User Pairing and Power Allocation for Throughput Maximization in NOMA Systems,” in Proc. IEEE ICC, Shanghai, China, May 2019.

  61. X. Zhang, X. Li, Y. Zhou, H. Qian, and X. Luo, “How to Exploit Mobility to Mitigate Pilot Contamination?,” in Proc. IEEE GlobalSIP, Anaheim, CA, Nov. 2018.

  62. Y. Zhou, V. W.S. Wong, and R. Schober, “Performance Analysis of Millimeter Wave NOMA Networks with Beam Misalignment,” in Proc. IEEE ICC, Kansas, MO, May 2018.

  63. Y. Zhou, V. W.S. Wong, and R. Schober, “Performance Analysis of Cooperative NOMA with Dynamic Decode-and-Forward Relaying,” in Proc. IEEE Globecom, Singapore, Dec. 2017.

  64. Y. Zhou and V. W.S. Wong, “Stable Throughput Region of Downlink NOMA Transmissions with Limited CSI,” in Proc. IEEE ICC, Paris, France, May 2017.

  65. A. Mostafa, Y. Zhou, and V. W.S. Wong, “Connectivity Maximization for Narrowband IoT Systems with NOMA,” in Proc. IEEE ICC, Paris, France, May 2017.

  66. Y. Zhou and W. Zhuang, “Beneficial Cooperation Ratio in Multi-Hop Wireless Ad Hoc Networks,” in Proc. IEEE INFOCOM, Turin, Italy, Apr. 2013.

  67. Y. Zhou, J. Liu, L. Zheng, and C. Zhai, “A Joint Scheduling and Transmission Power Control MAC Protocol for Wireless Ad Hoc Networks,” in Proc. IEEE WCSP, Nanjing, China, Nov. 2009.

Book Chapters

  1. Y. Zou, Y. Zhou, and Y. Shi, “Algorithm Unrolling for Massive Connectivity in IoT Networks,” Next Generation Multiple Access, Wiley-IEEE Press, 2023.

  2. Y. Zhou and W. Zhuang, “Interference Characterization for Cooperative Communication in Wireless Ad Hoc Networks,” Encyclopedia of Wireless Networks - Section “Interference Characterization and Mitigation”, Springer, doi:10.1007/978-3-319-32903-1, 2018.

  3. Y. Zhou and V. W.S. Wong, “Non-Orthogonal Multiple Access (NOMA),” Encyclopedia of Wireless Networks - Section “Interference Characterization and Mitigation”, Springer, doi:10.1007/978-3-319-32903-1 8-1, 2018.

  4. Y. Zhou, Z. Dai, X. Hao, M. Cheung, Z. Wang, and V. W.S. Wong, “Coalition Formation Games for Cooperative Spectrum Sensing in Cognitive Radio Networks,” Handbook of Cognitive Radio - Section “Cognitive Radio Resource Management”, Springer, pp. 1–32, May 2017.