Analysis and optimization of auto-correlation based frequency offset estimation

I. M. Ngebani, J. M. Chuma, S. Masupe

    Research output: Contribution to journalArticle

    Abstract

    In this letter, a general auto-correlation based frequency offset estimation (FOE) algorithm is analyzed. An approximate closed-form expression for the Mean Square Error (MSE) of the FOE is obtained, and it is proved that, given training symbols of fixed length N, choosing the number of summations in the auto-correlation to be (Formula presented.) and the correlation distance to be (Formula presented.) is optimal in that it minimizes the MSE. Simulation results are provided to validate the analysis and optimization.

    Original languageEnglish
    Pages (from-to)162-167
    Number of pages6
    JournalSAIEE Africa Research Journal
    Volume106
    Issue number3
    Publication statusPublished - Sep 1 2015

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    Autocorrelation
    Mean square error

    All Science Journal Classification (ASJC) codes

    • Electrical and Electronic Engineering

    Cite this

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    abstract = "In this letter, a general auto-correlation based frequency offset estimation (FOE) algorithm is analyzed. An approximate closed-form expression for the Mean Square Error (MSE) of the FOE is obtained, and it is proved that, given training symbols of fixed length N, choosing the number of summations in the auto-correlation to be (Formula presented.) and the correlation distance to be (Formula presented.) is optimal in that it minimizes the MSE. Simulation results are provided to validate the analysis and optimization.",
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    year = "2015",
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    pages = "162--167",
    journal = "Transactions of the South African Institute of Electrical Engineers",
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    Analysis and optimization of auto-correlation based frequency offset estimation. / Ngebani, I. M.; Chuma, J. M.; Masupe, S.

    In: SAIEE Africa Research Journal, Vol. 106, No. 3, 01.09.2015, p. 162-167.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Analysis and optimization of auto-correlation based frequency offset estimation

    AU - Ngebani, I. M.

    AU - Chuma, J. M.

    AU - Masupe, S.

    PY - 2015/9/1

    Y1 - 2015/9/1

    N2 - In this letter, a general auto-correlation based frequency offset estimation (FOE) algorithm is analyzed. An approximate closed-form expression for the Mean Square Error (MSE) of the FOE is obtained, and it is proved that, given training symbols of fixed length N, choosing the number of summations in the auto-correlation to be (Formula presented.) and the correlation distance to be (Formula presented.) is optimal in that it minimizes the MSE. Simulation results are provided to validate the analysis and optimization.

    AB - In this letter, a general auto-correlation based frequency offset estimation (FOE) algorithm is analyzed. An approximate closed-form expression for the Mean Square Error (MSE) of the FOE is obtained, and it is proved that, given training symbols of fixed length N, choosing the number of summations in the auto-correlation to be (Formula presented.) and the correlation distance to be (Formula presented.) is optimal in that it minimizes the MSE. Simulation results are provided to validate the analysis and optimization.

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    M3 - Article

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