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Research on Timing Synchronization Algorithm of Cell Search in 5G NR System

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Communications and Networking (ChinaCom 2020)

Abstract

For the 5G NR systems in the Third Generation Partnership Project(3GPP), the computation of synchronous signal detection algorithms is very complex. Based on the characteristics of the domain synchronous signal, this paper proposed a differential and superimposed interdependent cross correlation detection algorithm, which only performed a differential interdependent processing of the received signal with the sum of the local PSS sequence to obtain the position of the relevant peak and detects the position of the coarse synchronous point, and further performed local correlation of the coarse synchronous point, and detected the precise synchronous point according to the maximum peak, which reduced the computational complexity. A theoretical derivation and a comparative complexity analysis between the traditional cross correlation and the improved algorithms shows that the differential and superposition cross correlation joint detection algorithm has high efficiency, low complexity and strong resistance to frequency deviation, which meets the synchronization requirements of 5G NR systems.

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Acknowledgment

It is supported by the Science and Technology Major Project in Chongqing (R&D and application of 5G road test instruments: No. cstc2019jscx-zdztzxX0002).

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Correspondence to Hang Jiang .

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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Jiang, H., Cao, L., Zhang, Z., Deng, B. (2021). Research on Timing Synchronization Algorithm of Cell Search in 5G NR System. In: Gao, H., Fan, P., Wun, J., Xiaoping, X., Yu, J., Wang, Y. (eds) Communications and Networking. ChinaCom 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 352. Springer, Cham. https://doi.org/10.1007/978-3-030-67720-6_54

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  • DOI: https://doi.org/10.1007/978-3-030-67720-6_54

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67719-0

  • Online ISBN: 978-3-030-67720-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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