One of the major challenges in vehicle to everything (V2X) system is robust and low-cost synchronization for ultra-reliable low latency communication under various fading scenarios. To address this issue, this paper presents a maximum likelihood (ML) based algorithm for the sidelink secondary synchronization signal (S-SSS) detection, assuming the sidelink primary synchronization signal (S-PSS) detection has been successfully achieved at an earlier stage. Based on the specific signal structure, the proposed method exploits the channel selectivity in frequency domain (FD) and channel correlation in time domain (TD) to obtain an ML solution. In order to avoid the need to estimate the Doppler frequency and simplify the algorithm, we provide the ML solutions based on the assumptions of infinite or zero Doppler. Furthermore, we propose a practical method with limited TD channel taps that can be efficiently implemented in real systems. Simulation results show that the proposed method significantly improves the performance over the conventional detection methods under different Doppler scenarios.


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    Titel :

    A Maximum Likelihood Detection Method for NR Sidelink SSS Searcher


    Beteiligte:
    Lu, Sili (Autor:in) / Cheng, Hongbing (Autor:in) / Song, Kee-Bong (Autor:in)


    Erscheinungsdatum :

    01.04.2021


    Format / Umfang :

    5007360 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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