Non-stationarity Characteristics in Dynamic Vehicular ISAC Channels at 28 GHz

Zhang Zhengyu; He Ruisi; Yang Mi; Zhang Xuejian; Qi Ziyi; Mi Hang; Sun Guiqi; Yang Jingya; Ai Bo

doi:10.23919/cje.2024.00.003

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Zhengyu Zhang, Ruisi He, Mi Yang, et al., “Non-stationarity Characteristics in Dynamic Vehicular ISAC Channels at 28 GHz,” Chinese Journal of Electronics, vol. 34, no. 2, pp. 1–9, 2025 doi: 10.23919/cje.2024.00.003

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Zhengyu Zhang, Ruisi He, Mi Yang, et al., “Non-stationarity Characteristics in Dynamic Vehicular ISAC Channels at 28 GHz,” Chinese Journal of Electronics, vol. 34, no. 2, pp. 1–9, 2025 doi: 10.23919/cje.2024.00.003

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Non-stationarity Characteristics in Dynamic Vehicular ISAC Channels at 28 GHz

doi: 10.23919/cje.2024.00.003

Zhang Zhengyu^1
,,
He Ruisi^1
,,
Yang Mi^{1, 2
,
,},
Zhang Xuejian^1
,,
Qi Ziyi^1
,,
Mi Hang^1
,,
Sun Guiqi^1
,,
Yang Jingya^2
,,
Ai Bo^1
,

1.
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
2.
Henan High-Speed Railway Operation and Maintenance Engineering Research Center, Zhengzhou 451460, China

More Information

Author Bio:
Zhengyu Zhang received the B.S. and M.S. degrees in electronic and communication engineerin from Beijing Jiaotong University, China, in 2018 and 2021, respectively, where he is currently pursuing the Ph.D. degree in information and communication systems. His research interests include ISAC, wireless communications, channel characterization and modeling, deep learning, etc. (Email: zhengyu.zhang@bjtu.edu.cn)

Ruisi He received the B.E. and Ph.D. degrees from Beijing Jiaotong University (BJTU), Beijing, China, in 2009 and 2015, respectively. Dr. He is currently a Professor with the School of Electronics and Information Engineering, BJTU. His research interests include wireless propagation channels, railway and vehicular communications, 5G and 6G communications. He has authored/co-authored 8 books, 4 book chapters, more than 200 journal and conference papers. (Email: ruisi.he@bjtu.edu.cn)

Mi Yang received the M.S. and Ph.D. degrees from Beijing Jiaotong University, Beijing, China, in 2017 and 2021, respectively. He is currently an Associate Professor with School of Electronic Information Engineering, Beijing Jiaotong University, Beijing Jiaotong University. His research interests are focused on wireless channel measurement and modeling, vehicular and railway communications, and artificial intelligence (AI) in channel research. (Email: myang@bjtu.edu.cn)

Xuejian Zhang received the B.S. degree in communication engineering from Lanzhou Jiaotong University, Lanzhou, China, in 2021. He is currently pursuing the Ph.D degree with School of Electronic Information Engineering, Beijing Jiaotong University, Beijing, China. His research interests include wireless channel measurement and modeling, railway and vehicular communications and AI-based wireless channel modeling. (Email: 23115029@bjtu.edu.cn)

Ziyi Qi is currently pursuing the Ph.D degree with School of Electronic Information Engineering, Beijing Jiaotong University, Beijing, China. His research interests include wireless channel measurement and modeling, wireless propagation environment reconstruction and deterministic channel modeling. (Email: 22115006@bjtu.edu.cn)

Hang Mi received the B.S. degree in communication engineering from the North University of China, Taiyuan, China, in 2018. He is currently pursuing the Ph.D. degree with School of Electronic Information Engineering, Beijing Jiaotong University (BJTU), Beijing, China. His research interests include radio propagation channel models, millimeter-wave channel modeling, and machine learning in wireless channels. (Email: hangmi@bjtu.edu.cn)

Guiqi Sun received the B.E. degree from Qufu Normal University, Qufu, China, in 2016, the M.S. degree from Qingdao University, Qingdao, China, in 2019. She is currently working toward the Ph.D. degree with School of Electronic Information Engineering, Beijing Jiaotong University, Beijing, China. Her research interests include wireless propagation channel and reconfigurable intelligent surface channel modeling. (Email: guiqisun@bjtu.edu.cn)

Jingya Yang received the B.S. degree in communication engineering from Zhengzhou University, Zhengzhou, China, in 2010, and the M.S. degree in communication and information systems and the Ph.D. degree (Hons.) from Beijing Jiaotong University in 2013 and 2019, respectively. She is currently an Associate Professor with the Henan High-Speed Railway Operation and Maintenance Engineering Research Center. Her research interests include wireless channel measurement and modeling. (Email: yang_jing_ya@126.com)

Bo Ai received the M.S. and Ph.D. degrees from Xidian University, China. He was a Visiting Professor with the Electrical Engineering Department, Stanford University, Stanford, CA, USA, in 2015. He is currently a Full Professor with Beijing Jiaotong University. His research interests include the research and applications of channel measurement, channel modeling and dedicated mobile communications for rail traffic systems. (Email: boai@bjtu.edu.cn)
Corresponding author: Email: myang@bjtu.edu.cn
Received Date: 2024-01-03
Accepted Date: 2024-06-06

Available Online: 2024-07-22

Abstract

Abstract

Integrated sensing and communications (ISAC) is a potential technology of 6G, aiming to enable end-to-end information processing ability and native perception capability for future communication systems. As an important part of the ISAC application scenarios, ISAC aided vehicle-to-everything (V2X) can improve the traffic efficiency and safety through intercommunication and synchronous perception. It is necessary to carry out measurement, characterization, and modeling for vehicular ISAC channels as the basic theoretical support for system design. In this paper, dynamic vehicular ISAC channel measurements at 28 GHz are carried out and provide data for the characterization of non-stationarity characteristics. Based on the actual measurements, this paper analyzes the time-varying PDPs, RMSDS and non-stationarity characteristics of front, lower front, left and right perception directions in a complicated V2X scenarios. The research in this paper can enrich the investigation of vehicular ISAC channels and enable the analysis and design of vehicular ISAC systems.
- ISAC (integrated sensing and communication) channel,
- Millimeter wave,
- V2X,
- Channel measurement,
- Non-stationarity,
- Dynamic channel

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References(25)

References

[1]	C. Chen, C. Y. Wang, C. Li, et al., “A v2v emergent message dissemination scheme for 6G-oriented vehicular networks,” Chinese Journal of Electronics, vol. 32, no. 6, pp. 1179–1191, 2023. doi: 10.23919/cje.2022.00.337
[2]	Z. Y. Zhang, R. S. He, B. Ai, et al., “A general channel model for integrated sensing and communication scenarios,” IEEE Communications Magazine, vol. 61, no. 5, pp. 68–74, 2023. doi: 10.1109/MCOM.001.2200420
[3]	X. Meng, F. Liu, C. Masouros, et al., “Vehicular connectivity on complex trajectories: Roadway-geometry aware ISAC beam-tracking,” IEEE Transactions on Wireless Communications, vol. 22, no. 11, pp. 7408–7423, 2023. doi: 10.1109/TWC.2023.3250442
[4]	T. Luettel, M. Himmelsbach, and H. J. Wuensche, “Autonomous ground vehicles—concepts and a path to the future,” Proceedings of the IEEE, vol. 100, no. Special Centennial Issue, pp. 1831–1839, 2012. doi: 10.1109/JPROC.2012.2189803
[5]	Q. Liu, R. Luo, H. R. Liang, et al., “Energy-efficient joint computation offloading and resource allocation strategy for ISAC-aided 6G V2X networks,” IEEE Transactions on Green Communications and Networking, vol. 7, no. 1, pp. 413–423, 2023. doi: 10.1109/TGCN.2023.3234263
[6]	X. J. Li, J. Tang, Y. Xu, et al., “Mobility-aware multi-task migration and offloading scheme for internet of vehicles,” Chinese Journal of Electronics, vol. 32, no. 6, pp. 1192–1202, 2023. doi: 10.23919/cje.2022.00.333
[7]	L. H. Pang, J. Zhang, Y. Zhang, et al., “Investigation and comparison of 5G channel models: From QuaDRiGa, NYUSIM, and MG5G perspectives,” Chinese Journal of Electronics, vol. 31, no. 1, pp. 1–17, 2022. doi: 10.1049/cje.2021.00.103
[8]	R. S. He, C. Schneider, B. Ai, et al., “Propagation channels of 5G millimeter-wave vehicle-to-vehicle communications: Recent advances and future challenges,” IEEE Vehicular Technology Magazine, vol. 15, no. 1, pp. 16–26, 2020. doi: 10.1109/MVT.2019.2928898
[9]	X. J. Zhang, R. S. He, M. Yang, et al., “Measurements and modeling of large-scale channel characteristics in subway tunnels at 1.8 and 5.8 GHz,” IEEE Antennas and Wireless Propagation Letters, vol. 22, no. 3, pp. 561–565, 2023. doi: 10.1109/LAWP.2022.3218604
[10]	R. S. He, B. Ai, Z. D. Zhong, et al., “5G for railways: Next generation railway dedicated communications,” IEEE Communications Magazine, vol. 60, no. 12, pp. 130–136, 2022. doi: 10.1109/MCOM.005.2200328
[11]	L. Xiong, Z. Y. Zhang, and D. P. Yao, “Dynamic Doppler prediction in high-speed rail using long short-term memory neural network,” Transactions on Emerging Telecommunications Technologies, vol. 32, no. 9, article no. e4269, 2021. doi: 10.1002/ett.4269
[12]	Y. X. Zhang, R. S. He, B. Ai, et al., “Generative adversarial networks based digital twin channel modeling for intelligent communication networks,” China Communications, vol. 20, no. 8, pp. 32–43, 2023. doi: 10.23919/JCC.fa.2023-0206.202308
[13]	R. S. He, B. Ai, G. P. Wang, et al., “Wireless channel sparsity: Measurement, analysis, and exploitation in estimation,” IEEE Wireless Communications, vol. 28, no. 4, pp. 113–119, 2021. doi: 10.1109/MWC.001.2000378
[14]	J. L. Wang, J. H. Zhang, Y. X. Zhang, et al., “Empirical analysis of sensing channel characteristics and environment effects at 28 GHz,” in Proceedings of the 2022 IEEE Globecom Workshops (GC Wkshps ), Rio de Janeiro, Brazil, pp. 1323–1328, 2022.
[15]	Z. Y. Zhang, R. S. He, M. Yang, et al., “Millimeter wave channel measurements and analysis for integrated sensing and communication scenario,” in Proceedings of the 2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI ), Portland, USA, pp. 415–416, 2023.
[16]	Z. Y. Zhang, R. S. He, B. Ai, et al., “A shared multipath components evolution model for integrated sensing and communication channels,” IEEE Antennas and Wireless Propagation Letters, vol. 22, no. 12, pp. 2975–2978, 2023. doi: 10.1109/LAWP.2023.3307194
[17]	A. Ali, N. Gonzalez-Prelcic, R. W. Heath, et al., “Leveraging sensing at the infrastructure for mmWave communication,” IEEE Communications Magazine, vol. 58, no. 7, pp. 84–89, 2020. doi: 10.1109/MCOM.001.1900700
[18]	P. Q. Zhu, X. F. Yin, J. Rodríguez-Pineiro, et al., “Measurement based wideband space-time channel models for 77GHz automotive radar in underground parking lots,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 10, pp. 19105–19120, 2022. doi: 10.1109/TITS.2022.3157849
[19]	M. Yang, B. Ai, R. S. He, et al., “Vehicle-to-vehicle channel characteristics in intersection environment,” in Proceedings of the 2022 IEEE International Conference on Communications Workshops (ICC Workshops), Seoul, Korea, pp. 1124–1129, 2022.
[20]	P. Tang, R. Wang, A. F. Molisch, et al., “Path loss analysis and modeling for vehicle-to-vehicle communications in convoys in safety-related scenarios,” in Proceedings of the 2019 IEEE 2nd Connected and Automated Vehicles Symposium (CAVS), Honolulu, USA, pp. 1–6, 2019.
[21]	H. T. Chang, C. X. Wang, Y. Liu, et al., “A general 3-D nonstationary GBSM for underground vehicular channels,” IEEE Transactions on Antennas and Propagation, vol. 71, no. 2, pp. 1804–1819, 2023. doi: 10.1109/TAP.2022.3231679
[22]	Z. Y. Su, L. Liu, J. C. Zhang, et al., “Analysis of channel non-stationarity for V2V and V2I communications at 5.9GHz in urban scenarios,” in Proceedings of the 2022 IEEE International Conference on Communications Workshops (ICC Workshops), Seoul, Korea, pp. 1130–1134, 2022.
[23]	M. Yang, B. Ai, R. S. He, et al., “Non-stationary vehicular channel characterization in complicated scenarios,” IEEE Transactions on Vehicular Technology, vol. 70, no. 9, pp. 8387–8400, 2021. doi: 10.1109/TVT.2021.3096973
[24]	M. Herdin, N. Czink, H. Ozcelik, et al., “Correlation matrix distance, a meaningful measure for evaluation of non-stationary MIMO channels,” in Proceedings of the 2005 IEEE 61st Vehicular Technology Conference, Stockholm, Sweden, pp. 136–140, 2005.
[25]	T. T. Georgiou, “Distances and Riemannian metrics for spectral density functions,” IEEE Transactions on Signal Processing, vol. 55, no. 8, pp. 3995–4003, 2007. doi: 10.1109/TSP.2007.896119