Conference
Channel Estimation in Unknown Noise: Application of Canonical Correlation Decomposition in Subspaces
Abstract
The popular subspace algorithm proposed by Mouline et al. performs well when the channel output is corrupted by white noise. However, when the channel noise is correlated as is often encountered in practice, the standard subspace method degrades in performance. In this paper, based on second-order statistics and utilizing Canonical Correlation Decomposition (CCD) to obtain the subspaces, we develop two algorithms to blindly estimate the FIR …
Authors
He X; Wong KM
Volume
2
Pagination
pp. 475-478
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
January 1, 2005
DOI
10.1109/isspa.2005.1580978
Name of conference
Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005.