Publications
Selected Publications
[L23] D. Yuan, H. Zhou, X. Liu, H. Chen, Y. Xin, J. C. Zhang, “Enhancing Large Language Models (LLMs) for Telecom using Dynamic Knowledge Graphs and Explainable Retrieval-Augmented Generation,” IEEE Wireless Communications Magazine (Accepted), pp.1-10, Feb. 2026.
[L23] Y. Emami, H. Zhou, M. G. Gaitan, K. Li, L. Almeida, and Z. Han, “From Prompts to Protection: Large Language Model-enabled In-context Learning for Smart Public Safety UAV,” IEEE Wireless Communications Magazine (Accepted), pp.1-10, Feb. 2026.
[L22] Y. Emami, H. Zhou, M. G. Gaitan, K. Li, and L. Almeida, “Frsicl: LLM-enabled in-context learning flight resource allocation for fresh data collection in UAV-assisted wildfire monitoring,” IEEE Internet of Things Journal (Accepted), pp.1-10, Feb. 2025.
[P21] C. Hu, H. Zhou, D. Wu, X. Chen, J. Yan, and X. Liu, “Self-Refined Generative Foundation Models for Wireless Traffic Prediction,” IEEE Trans. on Vehicular Technology, pp.1-6, Nov. 2025.
[P20] Y. Emami, H. Zhou, S. Nabavirazani, and L. Almeida, “LLM-Enabled In-Context Learning for Data Collection Scheduling in UAV-assisted Sensor Networks,” IEEE Internet of Things Journal, pp.1-14, Sep. 2025.
[P19] Y. Lin*, H. Zhou*, C. Hu, X. Liu, H. Chen, Y. Xin, J. C. Zhang, “Hierarchical Debate-Based Large Language Model (LLM) for Complex Task Planning of 6G Network Management,” in International Conference on Machine Learning (ICML) 2025 Workshop on Machine Learning for Wireless Communication and Networks, Jun. 2025.
[P18] H. Zhou*, C. Hu*, D. Yuan, Y. Yuan, D. Wu, X. Liu, J. C. Zhang, “Prompting Wireless Networks: Reinforced In-Context Learning for Power Control,” in International Conference on Machine Learning (ICML) 2025 Workshop on Machine Learning for Wireless Communication and Networks, Jun. 2025.
[P17] Z. Yan*, H. Zhou*, J. Pei, H. Tabassum, “Hierarchical and Collaborative LLM-Based Control for Multi-UAV Motion and Communication in Integrated Terrestrial and Non-Terrestrial Networks,” in International Conference on Machine Learning (ICML) 2025 Workshop on Machine Learning for Wireless Communication and Networks, Jun. 2025.
[P16] H. Zhang, W. Wang, H. Zhou, Z. Lu, and Ming. Li, “Intelligent Attacks and Defense Methods in Federated Learning-enabled Energy-Efficient Wireless Networks,” IEEE Trans. on Wireless Communications, pp.1-15, Apr. 2025.
[P15] H. Zhang, W. Wang, H. Zhou, Z. Lu, and Ming. Li, “A Hierarchical DRL Approach for Resource Optimization in Multi-RIS Multi-Operator Networks,” IEEE Trans. on Wireless Communications, pp.1-15, Feb. 2025.
[P14] Z. Yan, H. Zhou, H. Tabassum, and X. Liu, “Hybrid LLM-DDQN based Joint Optimization of V2I Communication and Autonomous Driving,” IEEE Wireless Communications Letters, pp.1-5, Feb 2025.
[P13] H. Zhou, C. Hu, D. Yuan, Y. Yuan, D. Wu, X. Chen, H. Tabassum, X. Liu, “Large Language Models (LLMs) for Wireless Networks: An Overview from the Prompt Engineering Perspective,” IEEE Wireless Communications, pp.1-10, Jan. 2025.
[P12] H. Zhou, C. Hu, D. Yuan, Y. Yuan, D. Wu, X. Liu, Z. Han, and C. Zhang, “Generative AI as a Service in 6G Edge-Cloud: Generation Task Offloading by In-context Learning,” IEEE Wireless Communications Letters, pp.1-5, Dec. 2024.
[P11] M. A. Habib, H. Zhou, PE. Iturria-Rivera, M. Elsayed, M. Bavand, R. Gaigalas, Y. Ozcan, and M. Erol-Kantarci, “Machine Learning-enabled Traffic Steering in O-RAN: A Case Study on Hierarchical Learning Approach,” IEEE Communications Magazine, vol.63, no.1, pp. 100-107, Jan. 2025.
[P10] S. Salhi, H. Zhou, M. Elsayed, M. Bavand, R. Gaigalas, and M. Erol- Kantarci, “Jamming Attacks and Mitigation in Transfer Learning Enabled 5G RAN Slicing,” IEEE Trans. on Machine Learning in Communications and Networking, vol. 2, pp. 1492-1508, Sep. 2024.
[P09] H. Zhou, C. Hu, Y. Yuan, Y. Cui, Y. Jin, C. Chen, H. Wu, D. Yuan, L. Jiang, D. Wu, X. Liu, C. Zhang, X. Wang, and J. Liu, “Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunities,” IEEE Communications Survey & Tutorials, pp.1-52, Sep. 2024.
[P08] H. Zhou, M. Erol-Kantarci, Y. Liu, and H. V. Poor, “A Survey on Model-based, Heuristic, and Machine Learning Optimization Approaches in RIS-aided Wireless Networks,” IEEE Communications Survey & Tutorials, vol.26, no.2, pp.781-823, 2nd quarter, 2024.
[P07] H. Zhou, M. Erol-Kantarci, Y. Liu, and H. V. Poor, “Heuristic Algorithms for RIS-assisted Wireless Networks: Exploring Heuristic-aided Machine Learning,” IEEE Wireless Communications, vol.3, no.4, pp.1-9, Aug. 2024.
[P06] H. Zhou, M. Elsayed, M. Bavand, R. Gaigalas, S. Furr, and M. Erol-Kantarci, “Cooperative Hierarchical Deep Reinforcement Learning based Joint Sleep, Power, and RIS Control for Energy-Efficient RAN,” IEEE Trans. on Cognitive Communications and Networking, pp.1-15, Jul. 2024.
[P05] H. Zhang, H. Zhou, M. Elsayed, M. Bavand, R. Gaigalas, Y. Ozcan, and M. Erol-Kantarci, “On-Device Intelligence for 5G RAN: Knowledge Transfer and Federated Learning enabled UE-Centric Traffic Steering,” IEEE Trans. on Cognitive Communications and Networking, vol.10, no.2, pp. 689-705, Apr. 2023.
[P04] M. Razghandi, H. Zhou, M. Erol-Kantarci, and D. Turgut, “Smart Home Energy Management: VAE-GAN synthetic dataset generator and Q-learning,” IEEE Trans. on Smart Grid, vo.15, no.2, pp.1562-1573, May 2024.
[P03] H. Zhou, M. Erol-Kantarci, and H. V. Poor, “Knowledge Transfer and Reuse: A Case Study of AI-enabled Resource Management in RAN Slicing,” IEEE Wireless Communications, vol.30, no.5, pp.1-10, Oct. 2023.
[P02] H. Zhou, M. Erol-Kantarci, and H. V. Poor, “Learning from Peers: Deep Transfer Reinforcement Learning for Joint Radio and Cache Resource Allocation in 5G Network Slicing,” IEEE Trans. on Cognitive Communications and Networking, vol.8, no.4, pp.1925-1941, Dec.2022.
[P01] H. Zhou, A. Aral, I. Brandic, and M. Erol-Kantarci, “Multi-agent Bayesian Deep Reinforcement Learning for Microgrid Energy Management under Communication Failures,” IEEE Internet of Things Journal, vol.9, no.14, pp.11685-11698, Jul. 2022.