Satellite-ground integrated vehicular network can provision ubiquitous and unlimited network connectivity for massive vehicles, and is expected to play a vital role in 6G-supported intelligent transportation systems (ITS). However, due to its high-dynamic channel environments and limited satellite payload, the uplink synchronization has become a major bottleneck to restrict vehicular communication performance. Focusing on maintaining reliable uplink synchronization, we propose an efficient timing advance (TA) update approach in this paper. Specifically, an enhanced preamble format is first presented based on the periodical pairing sounding reference signals (SRSs), which enables the satellite to continuously track uplink timing variation with a low signaling overhead. By taking full advantage of all the fourth-order autocorrelation produces from the received preamble, we further design a novel timing metric consisted of the correlation and differential normalization functions, which is capable of having a considerably increased correlation length and shaper mainlobe, as compared to the existing ones. Through theoretical performance analysis, it is indicated that the proposed approach not only notably promotes class distance between the correct and wrong timing indexes, but also can achieve the immunity to multi-path effect and large carrier frequency offset (CFO), while having a reduced computational complexity. Simulation results in a typical low-earth-orbit (LEO) scenario reveal the superiority of our approach in terms of the false alarm probability, the missed detection probability, as well as the timing mean square error.


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    Title :

    Reliable Uplink Synchronization Maintenance for Satellite-Ground Integrated Vehicular Networks: A High-Order Statistics-Based Timing Advance Update Approach


    Contributors:
    Zhen, Li (author) / Wang, Yue (author) / Yu, Keping (author) / Lu, Guangyue (author) / Mumtaz, Zahid (author) / Wei, Wei (author)


    Publication date :

    2023-02-01


    Size :

    1898177 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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