K-Means Based Blind Noise Variance Estimation
K-Means Based Blind Noise Variance Estimation
- New search for: Selva, Esteban
- New search for: Kountouris, Apostolos
- New search for: Louet, Yves
- New search for: Selva, Esteban
- New search for: Kountouris, Apostolos
- New search for: Louet, Yves
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.
Document information
K-Means Based Blind Noise Variance Estimation
2021-04-01
3377668 byte
Conference paper
Electronic Resource
English
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