Project Description

Toward Untethered Extended Reality Through Wireless Sensing and Communications Co-design

The untethered XR project presents a cutting-edge solution for eliminating XR wired connections and limitations of XR user activity space by utilizing mmWave, machine learning, edge computing, and joint sensing and communications technologies to truly unleashing the high potential of XR. This project provides a rich environment and virtualized platform that facilitate educating and training students at multiple levels.

Feb. 1, 2025 ~ Jan. 31, 2028

Project Team

• Shiwen Mao

• Mingzhe Chen

Related Publications (journal & magazine)

• Z. Li, X. Luo, M. Chen, C. Xu, S. Mao, and Y. Liu, “Contextual combinatorial beam management via online probing for multiple access mmWave wireless networks,” IEEE Journal on Selected Areas in Communications, Special Issue on Next Generation Advanced Transceiver Technologies, to appear.

• Y. Yang, M. Chen, Y. Blankenship, J. Lee, Z. Ghassemlooy, J. Chen, and S. Mao, “Positioning using wireless networks: Applications, recent progress, and future challenges,” IEEE Journal on Selected Areas in Communications, Special Issue on Positioning and Sensing Over Wireless Networks, vol.42, no.9, pp.2149-2178, Sept. 2024. DOI: 10.1109/JSAC.2024.3423629.

• X. Li, M. Chen, Y. Hu, Z. Zhang, D. Liu, and S. Mao, “Jointly optimizing Terahertz based sensing and communications in vehicular networks: A dynamic graph neural network approach,” IEEE Transactions on Wireless Communications, vol.23, no.10, pp.12917-12932, Oct. 2024. DOI: 10.1109/TWC.2024.3397028.

• X. Li, M. Chen, Y. Liu, Z. Zhang, D. Liu, and S. Mao, “Graph neural networks for joint communications and sensing optimization in vehicular networks,” IEEE Journal on Selected Areas in Communications, Special Issue on 5G/6G Precise Positioning on Cooperative Intelligent Transportation Systems (C-ITS) and Connected Automated Vehicles (CAV), vol.41, no.12, pp.3893-3907, Dec. 2023. DOI: 10.1109/JSAC.2023.3322761.

Related Publications (conference)

• X. Li, M. Chen, Y. Hu, Z. Zhang, D. Liu, and S. Mao, “Dynamic graph neural networks for joint Terahertz based sensing and communication optimization in vehicular networks,” in Proc. IEEE WCNC 2024, Dubai, United Arab Emirates, Apr. 2024.

• X. Li, M. Chen, Z. Zhang, D. Liu, Y. Liu, and S. Mao, “Joint optimization of sensing and communciations in vehicular networks: A graph neural network based approach,” in Proc. IEEE ICC 2023, Rome, Italy, May/June 2023, pp.5781-5786.

We acknowledge the generous support from our sponsor

• National Science Foundation

This project is supported in part by the National Science Foundation under Grants CCSS-2434053 and CCSS-2434054. 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.