Publications

Below is a list of my research publications, including pre-prints, journal papers, and conference papers.
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Preprint

[3] K, Wu, Q. Zhao, J. Zhou, J. Wang, H. Qin†, X. Zhang, and X. Zhang, “Physics-Informed Deep Recurrent Back-Projection Network for Tunnel Propagation Modeling”, 2025. (corresponding author, under review)

[2] K, Wu, Q. Zhao, Z. Feng, H. Qin†, X. Zhang, and X. Zhang, “Intelligent Optimization of Wireless Access Point Deployment for Communication-Based Train Control Systems Using Deep Reinforcement Learning”, 2025. (corresponding author, under review)

[1] Y, Zhou, H, Wu, H. Qin†, X. Zhang, and X. Zhang, “Physics-Constrained Inc-GAN for Tunnel Propagation Modeling from Sparse Line Measurements”, 2025. (corresponding author, under review)

Journal Papers

[J16] S. A, L. D. Rienzo, H. Qin†, X. Zhu, X. Zhang, and L. Codecasa, “Multilevel Monte Carlo coupled with parabolic wave equation for uncertainty analysis in radio wave propagation,” IEEE Transactions on Antennas and Propagation, 2025. (corresponding author, early access)

[J15] K. Wu, K. Ni, H. Qin†, X. Zhang, and X. Zhang, “Efficient physics-based machine learning model for long-range radio wave propagation modeling in tunnels”, IEEE Transactions on Microwave Theory and Techniques, 2025. (corresponding author, early access)

[J14] Q. Zhang, B. Zhang, H. Qin†, X. Zhang, and X. Zhang, “Generalizable radio wave propagation modeling for long tunnels with stacked LSTM approach”, IEEE Antennas and Wireless Propagation Letters, 2025. (corresponding author, early access)

[J13] H. Qin, Z. Wu, Y. Liu, X. Zhang, and X. Zhang, “Physics-based trajectory design for cellular-connected UAV in rainy environments based on deep reinforcement learning,” IEEE Transactions on Intelligent Transportation Systems, vol. 26, no. 7, pp. 10320-10335, 2025.

[J12] S. Huang, H. Qin, W. Hou, X. Zhang, and X. Zhang, “Generalizable physics-guided convolutional neural network for irregular terrain propagation,” IEEE Transactions on Antennas and Propagation, vol. 73, no. 6, pp. 3975-3985, 2025.

[J11] H. Qin, W. Hou, X. Zhang, and X. Zhang, “Fast Parabolic Wave Equation-Based Time of Arrival Estimation Exploiting Sparse Matrices,” IEEE Antennas and Wireless Propagation Letters, vol. 24, no. 3, pp. 661-665, 2024.

[J10] S. Huang, H. Qin, and X. Zhang, “Efficient parabolic equation driven CNN propagation model in tunnels based on frequency conversion,” IEEE Transactions on Antennas and Propagation, vol. 72, no. 7, pp. 6024-6031, 2024.

[J9] Z. Zhao†, H. Qin†, J. Wang, W. Hou, X. Zhang, “Efficient propagation modelling for open‐confined mixed space using a hybrid ray‐tracing/waveguide theory method,” IET Microwaves, Antennas & Propagation, vol. 18, no. 8, pp. 608-617, 2024. (contributed equally)

[J8] H. Wu, T. Ding, H. Qin, and X. Zhang, “Efficient high-fidelity deep convolutional generative adversarial network model for received signal strength reconstruction in indoor environments,” Electronics Letters, vol. 60, no. 13, pp. e13265, 2024.

[J7] H. Qin and X. Zhang, “Comparative analysis of finite‐difference and split‐step based parabolic equation methods for tunnel propagation modelling,” IET Microwaves, Antennas & Propagation, vol. 18, no. 2, pp. 59-72, 2023.

[J6] H. Qin, S. Huang, and X. Zhang, “A high-accuracy deep back-projection CNN-based propagation model for tunnels,” IEEE Antennas and Wireless Propagation Letters, vol. 23, no. 3, pp. 1015-1019, 2023.

[J5] H. Wu, H. Qin, and X. Zhang, “Received signal strength reconstruction using Pix2Pix generative adversarial network,” Electronics Letters, vol. 59, no. 20, pp. e12988, 2023.

[J4] H. Qin and X. Zhang, “Physics‐based wave propagation model assisted vehicle localisation in tunnels,” IET Microwaves, Antennas & Propagation, vol. 17, no. 10, pp. 786-796, 2023.

[J3] H. Qin and X. Zhang, “Efficient radio wave propagation modeling in tunnels with a sparse Fourier transform-based split-step parabolic equation method,” IEEE Antennas and Wireless Propagation Letters, vol. 22, no. 10, pp. 2442-2446, 2023.

[J2] Z. Zhao†, H. Qin†, J. Wang, W. Hou, X. Zhang, “Embedding antennas with tilted beam patterns into parabolic wave equation-based models for tunnel propagation,” IET Microwaves, Antennas & Propagation, vol. 17, no. 9, pp. 685-693, 2023. (contributed equally)

[J1] H. Qin, S. Huang, and X. Zhang, “Efficient physics-based recurrent neural network model for radio wave propagation in tunnels at 2.4 GHz,” Electronics Letters, vol. 59, no. 8, pp. e12789, 2023.

Conference Papers

[C24] J. Zhou, K. Wu, Q. Zhao, L. Zhang, and H. Qin, “A PSO-Based TOA–FOA Fusion Method for TDMA Acoustic Localization”, 2025 International Conference on Information Automation, 2025. (accepted)

[C23] H. Qin, S. Huang, Y. Mu, X. Zhang, and X. Zhang, “Parabolic Wave Equation Approaches for Tunnel Propagation Modeling: An Overview for 5G and Beyond Wireless Communications”, 2025 IEEE 102nd Vehicular Technology Conference, 2025. (accepted)

[C22] H. Qin, Y. Mu, X. Zhang, and X. Zhang, “Physics-informed Deep Reinforcement Learning for Optimal Wireless Access Point Deployment in Railway Environments”, Photonics & Electromagnetics Research Symposium (PIERS), 2025. (accepted)

[C21] H. Qin, Y. Mu, S. Huang, X. Zhang, and X. Zhang, “Modeling Radio Wave Propagation over Irregular Terrain via the Split-step Parabolic Equation Approach”, Photonics & Electromagnetics Research Symposium (PIERS), 2025. (accepted)

[C20] H. Wu, H. Qin, S. Huang, S. Ma, X. Zhang, and X. Zhang, “Efficient Radio Wave Propagation Prediction Using Dynamic GAN-based Model with Data Augmentation”, Photonics & Electromagnetics Research Symposium (PIERS), 2025. (accepted)

[C19] S. Yang, S. Huang, H. Qin, X. Zhang, and X. Zhang, “A Statistically-bounded Machine Learning Framework for Robust Full-wave Electromagnetic Inversion”, Photonics & Electromagnetics Research Symposium (PIERS), 2025. (accepted)

[C18] Y. Mu, H. Qin, X. Zhang, and X. Zhang, “A Statistically-bounded Machine Learning Framework for Robust Full-wave Electromagnetic Inversion”, Photonics & Electromagnetics Research Symposium (PIERS), 2025. (accepted)

[C17] S. Yang, S. Huang, H. Qin, S. Yang, X. Zhang, and X. Zhang, “Frequency-Tunable CNN Model for Radio Wave Propagation in Tunnel Environments,” IEEE MTT-S International Wireless Symposium, 2025.

[C16] S. Yang, S. Huang, H. Qin, X. Zhang, and X. Zhang, “Split-Step Parabolic Equation Driven CNN Model for Radio Wave Propagation Over Complex Terrain,” IEEE MTT-S International Wireless Symposium, 2025.

[C15] H. Xu, J. Wang, K. Wu, Q. Zhao, H. Qin, X. Zhang, and X. Zhang, “A Temporal Attention Unit-Based Machine Learning Model for Efficient Radio Wave Propagation Prediction in Tunnels,” IEEE MTT-S International Wireless Symposium, 2025.

[C14] Y. Yin and H. Qin, “Approximate signal detection for massive MIMO: Neumann series, iterative techniques, and machine learning enhancements,” 5th International Conference on Signal Processing and Machine Learning, 2025.

[C13] H. Qin and X. Zhang, “Parabolic equation-based channel model for RIS-aided train communication systems,” Photonics & Electromagnetics Research Symposium (PIERS), 2024.

[C12] H. Qin, S. An, and X. Zhang, “Efficient two-way parabolic equation method with sparse Fourier transform for radio wave propagation over irregular terrain,” Photonics & Electromagnetics Research Symposium (PIERS), 2024.

[C11] S. An, H. Qin, and X. Zhang, “Efficient uncertainty quantification with subspace pursuit for FDTD based microwave circuit models,” Photonics & Electromagnetics Research Symposium (PIERS), 2024.

[C10] H. Qin, Z. Wu, and X. Zhang, “Path planning for cellular-connected UAV using parabolic equation-based radio wave propagation models,” Photonics & Electromagnetics Research Symposium (PIERS), 2023.

[C9] H. Wu, H. Qin, S. Ma, H-D. Lang, and X. Zhang, “Received signal strength prediction using generative adversarial networks for indoor localization,” Photonics & Electromagnetics Research Symposium (PIERS), 2023.

[C8] H. Qin and X. Zhang, “Two-way parabolic equation method for millimeter-wave propagation modeling in tunnels,” 2022 IEEE 8th International Conference on Computer and Communications (ICCC), 2022.

[C7] H. Qin and X. Zhang, “Modeling of millimeter-wave propagation in tunnels with split-step parabolic equation method,” IEEE Topical Conference on Antennas and Propagation in Wireless Communications (ICEAA IEEE-APWC), 2022.

[C6] H. Qin, W. Hou, J. Du, S. Yang, X. Zhang, “Parabolic equation-based channel model for direction of arrival estimation in indoor environments,” IEEE International Symposium on Antennas and Propagation (AP-S), 2022.

[C5] S. Wang, S. Huang, H. Wu, H. Qin, X. Zhang, “Vector parabolic equation driven CNN models for radio wave propagation in tunnels,” IEEE International Symposium on Antennas and Propagation (AP-S), 2022.

[C4] H. Qin, W. Hou, J. Du, S. Yang, X. Zhang, “Numerical evaluation of impacts of dust and water vapor on indoor channel characteristics,” IEEE International Symposium on Antennas and Propagation (AP-S), 2021.

[C3] H. Qin, W. Hou, J. Du, S. Yang, X. Zhang, “Study of dust effect on radio wave propagation at sub-6 GHz in industrial environments,” International Union of Radio Science General Assembly & Scientific Symposium (URSI-GASS), 2021.

[C2] H. Qin and X. Zhang, “Efficient modeling of radio wave propagation in tunnels for 5G and beyond using a split-step parabolic equation method,” International Union of Radio Science General Assembly & Scientific Symposium (URSI-GASS), 2021.

[C1] H. Qin, S. Shi, and X. Tong, “A new weighted indoor positioning algorithm based on the physical distance and clustering,” 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), 2019.