Accession Number:

ADA091346

Title:

A Least Squares Adaptive Lattice Equalizer Algorithm.

Descriptive Note:

Technical rept. Oct 78-Sep 79,

Corporate Author:

NAVAL OCEAN SYSTEMS CENTER SAN DIEGO CA

Personal Author(s):

Report Date:

1980-09-02

Pagination or Media Count:

23.0

Abstract:

In many applications of adaptive data equalization, rapid initial convergence of the adaptive equalizer is of paramount importance. Apparently the fastest known equalizer adaptation algorithm is based on a least squares estimation algorithm. The least squares algorithm, which is a special case of the Kalman estimation algorithm, was first applied to channel equalization by Godard in a seminal paper. One disadvantage with the Godard algorithm is that the complexity, i.e., number of additions and multiplications, of the algorithm grows quadradically with the number of filter coefficients. Recently, however, Morf, Ljung, Lee and others have shown how the complexity of the conventionally implemented least squares algorithms e.g., Godards algorithm can be made to grow only linearly with the number of filter coefficients. Furthermore, these computationally simpler least squares algorithms may be implemented either in tapped delay line or lattice form. The application of the tapped delay line form, i.e., the fast Kalman algorithm, to channel equalization has been considered recently by Falconer and Ljung. In this paper, it is shown how the least squares lattice algorithms originally introduced by Morf and Lee can be adapted to the equalizer adjustment algorithm. The extremely rapid start up convergence properties of the least squares lattice equalizer are confirmed by computer simulation. Author

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE