Project Description
Learning-Assisted Integrated Sensing, Communication and Security for 6G UAV Networks
The project aims to develop deep learning (DL)-based localization and sensing in UAV mmWave networks, location-aided UAV mmWave communications, and joint UAV mmWave communication and radar co-design to improve mmWave spectrum utilization, wireless sensing performance, and UAV device security. The research agenda consists of five well integrated thrusts: (i) Learning-based mmWave UAV localization and wireless sensing; (ii) Joint design of location-aided UAV mmWave communications and sensing; (iii) Multiple UAV communications and sensing co-design; (iv) Learning-based RF fingerprinting for UAV security; and (v) Integration and assessment.
Oct. 1, 2024 ~ Sept. 30, 2027
Project Team
Related Publications (journal & magazine)
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J. Wang, C. Qi, S. Yu, and S. Mao, “Joint beamforming and illumination pattern design for beam-hopping LEO satellite communications,” IEEE Transactions on Wireless Communications, to appear. DOI: 10.1109/TWC.2024.3463002.
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C. Lei, W. Feng, P. Wei, H. Chen, N. Ge, and S. Mao, “Edge information hub: Orchestrating satellites, UAVs, MEC, sensing and communications for 6G closed-loop controls,” IEEE Journal on Selected Areas in Communications, Special Issue on Integrated Ground-Air-Space Wireless Networks for 6G Mobiles, to appear. DOI: 10.1109/JSAC.2024.3460053.
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C. Zhan, H. Hu, J. Wang, Z. Liu, and S. Mao, “Tradeoff between age of information and operation time for UAV sensing over multi-cell cellular networks,” IEEE Transactions on Mobile Computing, vol.23, no.4, pp.22976-2991, Apr. 2024. DOI: 10.1109/TMC.2023.3267656.
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P. Wei, W. Feng, Y. Chen, N. Ge, W. Xiang, and S. Mao, “Task-oriented satellite-UAV networks with mobile edge computing,” IEEE Open Journal of the Communications Society, vol.5, pp.202-220, Jan. 2024. DOI: 10.1109/OJCOMS.2023.3341251.
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A. Bera, S. Misra, C. Chatterjee, and S. Mao, “CEDAN: Cost-effective data aggregation for UAV-enabled IoT networks,” IEEE Transactions on Mobile Computing, vol.22, no.9, pp.5053-5063, Sept. 2023. DOI: 10.1109/TMC.2022.3172444.
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S. Misra, P. Kumar Deb, N. Koppala, A. Mukherjee, and S. Mao, “S-Nav: Safety-aware IoT navigation tool for avoiding COVID-19 hotspots,” IEEE Internet of Things Journal, vol.8, no.8, pp. 6975-6982, Apr. 2021. DOI: 10.1109/JIOT.2020.3037641.
Related Publications (conference)
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C. Lei, W. Feng, P. Wei, Y. Chen, N. Ge, and S. Mao, “Joint resource allocation and data offloading for closed-loop controls in satellite-UAV networks,” in Proc. 2024 International Conference on Wireless Communications and Signal Processing (WCSP), Hefei, China, Oct. 2024.
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T. Zhao, M. Wang, S. Mao, and X. Wango, “Few-shot learning and data augmentation for cross-domain UAV fingerprinting,” in Proc. ACM Mobicom 2024 Workshop on Machine Learning for NextG Networks (MLNextG24), Washington, D.C., Nov. 2024.
We acknowledge the generous support from our sponsor
This work is supported in part by the U.S. National Science Foundation (NSF) under Grant CNS-2415208. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the foundation.