Integrated sensing and communication (ISAC) is recognized as a promising solution for realizing sensing and communication functionalities in future vehicular networks. In addition, collision avoidance (CA) techniques are considered imperative to address the prevailing challenges of traffic safety. In this article, we propose an ISAC-assisted CA vehicle-to-infrastructure (V2I) system. In this system, environmental sensing is achieved by utilizing signal echoes, while the subject vehicle simultaneously establishes communication with the base station. To address the issue of spectrum scarcity, both communication and sensing functionalities are implemented in the millimeter-wave (mmWave) frequency band. To compensate for the high path loss associated with mmWave, we employ multiple-input multiple-output (MIMO) and beamforming techniques. Unlike existing multi-radar CA systems, ISAC technology enables sensing functionality by using a single device. However, the application of a single device results in the reduced signal coverage area, necessitating multi-directional scanning for improved environmental sensing. To this end, we commence by defining a signal scanning area, endowed with the ability to dynamically adjust the scanning distance in alignment with the scanning direction and vehicle speed. Moreover, we apply radar imaging to discern the rotation attitude of the target, thereby elevating target tracking precision and enhancing driving safety. To further improve the energy efficiency of the CA system, we propose a novel power allocation (PA) scheme between the communication system and the radar system. Simulation results demonstrate the feasibility and practicability of the proposed method concerning scanning area and attitude recognition. Furthermore, these results prove that the proposed PA scheme enhances the communication rate while ensuring the sensing performance.


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    Titel :

    ISAC-Assisted Collision Avoidance Mechanism for Vehicle-to-Infrastructure Systems


    Beteiligte:
    Ye, Zhong (Autor:in) / Yu, Changhong (Autor:in) / Zhu, Haiyun (Autor:in) / He, Yinghui (Autor:in) / Gao, Ming (Autor:in) / Yu, Guanding (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.10.2024


    Format / Umfang :

    4083413 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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