Chirp Delay-Doppler Domain Modulation: A New Paradigm of Integrated Sensing and Communication for Autonomous Vehicles

Autonomous driving is reshaping the way humans travel, with millimeter wave (mmWave) radar playing a crucial role in this transformation to enable 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: https://github.com/LiZhuoRan0.

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Publication Details

Journal
IEEE Network
Published
2025-05-26
DOI
https://doi.org/10.1109/mnet.2025.3573832
Citations
4
Primary Topic
Wireless Body Area Networks
Type
article
Field-Weighted Citation Impact
2.70
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article

Chirp Delay-Doppler Domain Modulation: A New Paradigm of Integrated Sensing and Communication for Autonomous Vehicles

Zhonghuai Wu, Shufeng Tan, Zhen Gao, Yi Tao et al.
4 citations
IEEE Network
Wireless Body Area Networks
2.70
article

Chirp Delay-Doppler Domain Modulation: A New Paradigm of Integrated Sensing and Communication for Autonomous Vehicles

Zhonghuai Wu, Shufeng Tan, Zhen Gao, Yi Tao, Dezhi Zheng, Chun Hu, Zhuoran Li, Zhongxiang Li
article en
4 citations

Abstract

Autonomous driving is reshaping the way humans travel, with millimeter wave (mmWave) radar playing a crucial role in this transformation to enable 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: https://github.com/LiZhuoRan0.

IEEE NetworkVol. 39(6)
Beijing Institute of Technology (CN)
Openalex Percentile: Top 10%
Wireless Body Area Networks
2.70
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