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Blind noise and channel estimation

Abstract : In the classical methods for blind channel identification (subspace method, TXK, XBM) (Moulines et al, 1995; Tong et al, 1994; Xavier et al, 1997), the additive noise is assumed to be spatially white or known to within a multiplicative scalar. When the noise is non-white (colored or correlated) but has a known covariance matrix, we can still handle the problem through prewhitening. However, there are no techniques presently available to deal with completely unknown noise fields. It is well known that when the noise covariance matrix is unknown, the channel parameters may be grossly inaccurate. In this paper, we assume the noise is spatially correlated, and we apply this assumption for blind channel identification. We estimate the noise covariance matrix without any assumption except its structure which is assumed to be a band-Toeplitz matrix. The performance evaluation of the developed method and its comparison to the modified subspace approach (MSS) (Abed-Meraim et al, 1997) are presented.
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Contributor : Miloud Frikel <>
Submitted on : Friday, June 22, 2018 - 3:03:19 PM
Last modification on : Friday, November 22, 2019 - 4:34:48 PM



M. Frikel, W. Utschick, J. Nossek. Blind noise and channel estimation. Tenth IEEE Workshop on Statistical Signal and Array Processing, Aug 2000, Pocono Manor, United States. ⟨10.1109/SSAP.2000.870099⟩. ⟨hal-01821521⟩



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