Auto-Correlation Based Frequency Offset Estimation Algorithm for 5G NR System 


Vol. 45,  No. 10, pp. 1676-1680, Oct.  2020
10.7840/kics.2020.45.10.1676


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  Abstract

In 5G NR system, mobile stations should achieve cell identification and time, frequency synchronizations with periodically broadcasted synchronization signal block (SSB) which consists of primary and secondary synchronization signals and physical broadcast channel. Each SSB contains one of three possible primary synchronization signals which is used to estimate initial carrier frequency offset and thus, cross-correlation based frequency offset estimation algorithm requires three correlators. In addition, if a frequency offset hypothesis scheme jointly used to increase the range of frequency offset estimation, the required complexity for the cross-correlation based estimator increases drastically. In this paper, we propose an auto-correlation based frequency offset estimation algorithm which exploits the complex conjugate centrally symmetric property of time-domain primary synchronization signal. Unlike the cross correlation based estimator, the proposed algorithm requires only one correlator for frequency offset estimation and thus, requires relatively very low computational complexity.

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  Cite this article

[IEEE Style]

M. So and W. Oh, "Auto-Correlation Based Frequency Offset Estimation Algorithm for 5G NR System," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 10, pp. 1676-1680, 2020. DOI: 10.7840/kics.2020.45.10.1676.

[ACM Style]

Minseok So and Wangrok Oh. 2020. Auto-Correlation Based Frequency Offset Estimation Algorithm for 5G NR System. The Journal of Korean Institute of Communications and Information Sciences, 45, 10, (2020), 1676-1680. DOI: 10.7840/kics.2020.45.10.1676.

[KICS Style]

Minseok So and Wangrok Oh, "Auto-Correlation Based Frequency Offset Estimation Algorithm for 5G NR System," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 10, pp. 1676-1680, 10. 2020. (https://doi.org/10.7840/kics.2020.45.10.1676)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880