Blind noise and channel estimation

In the classical methods for blind channel identification (Subspace method, TXK, XBM) [1, 2, 3], the additive noise is assumed to be spatially white or known to within a multiplicative scalar. When the noise is nonwhite (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 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) [4] are presented.