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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.16807 |
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| _version_ | 1866912387774283776 |
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| author | Li, Zhuoran Tan, Shufeng Gao, Zhen Tao, Yi Wu, Zhonghuai Li, Zhongxiang Hu, Chun Zheng, Dezhi |
| author_facet | Li, Zhuoran Tan, Shufeng Gao, Zhen Tao, Yi Wu, Zhonghuai Li, Zhongxiang Hu, Chun Zheng, Dezhi |
| contents | Autonomous driving is reshaping the way humans travel, with millimeter wave (mmWave) radar playing a crucial role in this transformation to enabe vehicle-to-everything (V2X). Although chirp is widely used in mmWave radar systems for its strong sensing capabilities, the lack of integrated communication functions in existing systems may limit further advancement of autonomous driving. In light of this, we first design ``dedicated chirps" tailored for sensing chirp signals in the environment, facilitating the identification of idle time-frequency resources. Based on these dedicated chirps, we propose a chirp-division multiple access (Chirp-DMA) scheme, enabling multiple pairs of mmWave radar transceivers to perform integrated sensing and communication (ISAC) without interference. Subsequently, we propose two chirp-based delay-Doppler domain modulation schemes that enable each pair of mmWave radar transceivers to simultaneously sense and communicate within their respective time-frequency resource blocks. The modulation schemes are based on different multiple-input multiple-output (MIMO) radar schemes: the time division multiplexing (TDM)-based scheme offers higher communication rates, while the Doppler division multiplexing (DDM)-based scheme is suitable for working in a lower signal-to-noise ratio range. We then validate the effectiveness of the proposed DDM-based scheme through simulations. Finally, we present some challenges and issues that need to be addressed to advance ISAC in V2X for better autonomous driving. Simulation codes are provided to reproduce the results in this paper: \href{https://github.com/LiZhuoRan0/2025-IEEE-Network-ChirpDelayDopplerModulationISAC}{https://github.com/LiZhuoRan0}. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_16807 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Chirp Delay-Doppler Domain Modulation: A New Paradigm of Integrated Sensing and Communication for Autonomous Vehicles Li, Zhuoran Tan, Shufeng Gao, Zhen Tao, Yi Wu, Zhonghuai Li, Zhongxiang Hu, Chun Zheng, Dezhi Signal Processing Autonomous driving is reshaping the way humans travel, with millimeter wave (mmWave) radar playing a crucial role in this transformation to enabe vehicle-to-everything (V2X). Although chirp is widely used in mmWave radar systems for its strong sensing capabilities, the lack of integrated communication functions in existing systems may limit further advancement of autonomous driving. In light of this, we first design ``dedicated chirps" tailored for sensing chirp signals in the environment, facilitating the identification of idle time-frequency resources. Based on these dedicated chirps, we propose a chirp-division multiple access (Chirp-DMA) scheme, enabling multiple pairs of mmWave radar transceivers to perform integrated sensing and communication (ISAC) without interference. Subsequently, we propose two chirp-based delay-Doppler domain modulation schemes that enable each pair of mmWave radar transceivers to simultaneously sense and communicate within their respective time-frequency resource blocks. The modulation schemes are based on different multiple-input multiple-output (MIMO) radar schemes: the time division multiplexing (TDM)-based scheme offers higher communication rates, while the Doppler division multiplexing (DDM)-based scheme is suitable for working in a lower signal-to-noise ratio range. We then validate the effectiveness of the proposed DDM-based scheme through simulations. Finally, we present some challenges and issues that need to be addressed to advance ISAC in V2X for better autonomous driving. Simulation codes are provided to reproduce the results in this paper: \href{https://github.com/LiZhuoRan0/2025-IEEE-Network-ChirpDelayDopplerModulationISAC}{https://github.com/LiZhuoRan0}. |
| title | Chirp Delay-Doppler Domain Modulation: A New Paradigm of Integrated Sensing and Communication for Autonomous Vehicles |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2505.16807 |