Research

My research focuses on intelligent and secure wireless communications, by exploring the synergy between theoretical research and experimental investigation. More specifically, I conduct research on the performance modeling and analysis of large-scale beyond 5G/6G multi-band heterogeneous wireless networks. Additionally, I am working towards machine learning enabled intelligent network optimization with applications to massive MIMO and intelligent reflecting surface (IRS). Finally, I develop secure physical layer key generation protocols based on wireless channels. I have (co)-authored 15+ papers in top-tier IEEE journals and conferences.

Modeling and Analysis of Large-scale Beyond 5G/6G Networks

• Y. Wang, C. Chen^* and X. Chu, “Performance analysis for hybrid mmWave and THz networks with downlink and uplink decoupled cell association,” submitted to IEEE Transactions on Wireless Communications. arXiv
• C. Chen, J. Zhang, X. Chu and J. Zhang, “On the deployment of small cells in 3D HetNets with multi-antenna base stations,” IEEE Trans. Wireless Commun., vol. 21, no. 11, pp. 9761-9774, Nov. 2022. PDF
• C. Chen, J. Zhang, X. Chu and J. Zhang, “On the optimal base-station height in mmWave small-cell networks considering cylindrical blockage effects,” IEEE Trans. Veh. Technol., vol. 70, no. 9, pp. 9588-9592, Sept. 2021. PDF
• Y. Wang, C. Chen^*, H. Zheng and X. Chu, “Performance of indoor small-cell networks under interior wall penetration losses,” IEEE Internet Things J., vol. 10, no. 12, pp. 10907-10915, Jun. 2023. PDF
• C. Chen, Y. Zhang, J. Zhang, X. Chu and J. Zhang, “On the performance of indoor multi-story small-cell networks,” IEEE Trans. Wireless Commun., vol. 20, no. 2, pp. 1336-1348, Feb. 2021. PDF
• M. Zhou, C. Chen and X. Chu, “Impact of 3D antenna radiation pattern on heterogeneous cellular networks,” IEEE Access, vol. 10, pp. 120866-120879, 2022. PDF

Machine Learning for Wireless Communications and Security

• L. Wang, C. Chen^*, C. Fischione and J. Zhang, “Learning-based joint antenna selection and precoding design for cell-free MIMO networks,” submitted to IEEE Transactions on Wireless Communications. arXiv
• C. Chen, S. Xu, J. Zhang and J. Zhang, “A distributed machine learning-based approach for IRS-enhanced cell-free MIMO networks,” IEEE Trans. Wireless Commun., accepted. PDF
• C. Chen, J. Zhang, T. Lu, M. Sandell and L. Chen, “Secret key generation for IRS-assisted multi-antenna systems: A machine learning-based approach,” IEEE Trans. Inf. Forensics Secur., accepted. PDF
• C. Chen, J. Zhang, T. Lu, M. Sandell and L. Chen, “Machine learning-based secret key generation for IRS-assisted multi-antenna systems,” accepted by IEEE International Conference on Communication (ICC) 2023. PDF

Secure Physical Layer Key Generation Based on Wireless Channels

• C. Chen, J. Zhang and Y. Chen, “Adaptive quantization for key generation in low-power wide-area networks,” arXiv
• C. Chen, J. Zhang, T. Lu, M. Sandell and L. Chen, “Secret key generation for IRS-assisted multi-antenna systems: A machine learning-based approach,” IEEE Trans. Inf. Forensics Secur., accepted. PDF
• T. Lu, L. Chen, J. Zhang, C. Chen and A. Hu, “Joint precoding and phase shift design in reconfigurable intelligent surfaces-assisted secret key generation,” IEEE Trans. Inf. Forensics Secur., vol. 18, pp. 3251-3266, 2023. PDF
• T. Lu, L. Chen, J. Zhang, C. Chen and T. Q. Duong, “Reconfigurable intelligent surface-assisted key generation for millimeter wave communications,” 2023 IEEE Wireless Communications and Networking Conference (WCNC), 2023, pp. 1-6. PDF
• T. Lu, L. Chen, J. Zhang, C. Chen, T. Q. Duong and M. Matthaiou, “Precoding design for key generation in near-field extremely large-scale MIMO communications,” accepted by 2023 IEEE Globecom Workshops.