Title :
Asymptotic analysis of reduced rank Wiener filters
Author :
Loubaton, Philippe ; Hachem, Walid
Author_Institution :
Lab. Traitement et Commun. de I´´Inf., Univ. de Marne-la-Vallee, France
Abstract :
We revisit recent papers of M.L. Honig and W. Xiao (see IEEE Trans. on Inf. Theory, vol.47, no.5, p.1928-46, 2001) and L.G.F. Trichard et al. (see Proc. IEEE Int. Conf. on Commun., p.1461-5, 2002; Proc. ISIT 2002) devoted to the asymptotic analysis of reduced rank Wiener filters. Appropriate connections between the asymptotic behavior of the signal-to-noise ratios (SNRs) at the outputs of these filters and the theory of orthogonal polynomials for the power moment problem are established. Using some classical results of this theory, it can be established, in particular, that the reduced rank filter output SNR converges exponentially in the filter rank toward the full rank Wiener filter output SNR. The convergence rate is given. Interestingly, it depends only on the support of the limiting eigenvalue distribution of the observation covariance matrix, but not on its particular form.
Keywords :
Wiener filters; convergence of numerical methods; covariance matrices; eigenvalues and eigenfunctions; multidimensional signal processing; polynomials; SNR; asymptotic analysis; eigenvalue distribution; multidimensional signal processing; observation covariance matrix; orthogonal polynomials; power moment problem; reduced rank Wiener filters; reduced rank filter; signal-to-noise ratio; Convergence; Covariance matrix; Eigenvalues and eigenfunctions; Equations; Filtering theory; Limiting; Multidimensional signal processing; Polynomials; Signal to noise ratio; Wiener filter;
Conference_Titel :
Information Theory Workshop, 2003. Proceedings. 2003 IEEE
Print_ISBN :
0-7803-7799-0
DOI :
10.1109/ITW.2003.1216760