When an unknown signal propagates through an AWGN channel of unknown variance, estimating the noise variance can be difficult. We propose a novel method to perform blind noise variance estimation, based on the separation of noise-only values and signal-plus-noise values in the frequency representation of the received signal. This separation is conducted using the K-means algorithm. Our linear-complexity method is efficient and accurate, requires a limited amount of samples and is robust to SNRs as low as −7 dB. It relies on two weak hypotheses of compacity and sparsity on the signal of interest.


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    Titel :

    K-Means Based Blind Noise Variance Estimation


    Beteiligte:
    Selva, Esteban (Autor:in) / Kountouris, Apostolos (Autor:in) / Louet, Yves (Autor:in)


    Erscheinungsdatum :

    01.04.2021


    Format / Umfang :

    3377668 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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