Title :
Improved Mean-Square Error Estimate for the LMS Transversal Equalizer With Narrowband Interference
Author :
Ikuma, T. ; Beex, A.A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Louisiana State Univ., Baton Rouge, LA
Abstract :
When the least-mean-square (LMS) algorithm is used to adapt an adaptive transversal equalizer that is subject to strong narrowband interference, a so-called non-Wiener or nonlinear effect takes place. This results in the mean-square error (MSE) performance of the adaptive equalizer being better than that of the fixed Wiener filter of equivalent structure. Reuter and Zeidler proposed a transfer-function-based approach to provide an estimate of the MSE performance of the equalizer in such an environment. We have recently shown that the mean of the LMS weights in this adaptive equalizer problem shifts away from the Wiener filter solution. As a result, we propose an MSE model for the LMS equalizer that is an improvement over the existing Reuter-Zeidler model. The new model uses the same transfer-function-based approach but incorporates the shift in the mean of the weights. Numerical simulations are provided to illustrate the improvement.
Keywords :
Wiener filters; adaptive equalisers; filtering theory; least mean squares methods; LMS algorithm; MSE performance; Reuter-Zeidler model; Wiener filter; adaptive transversal equalizer; least-mean-square algorithm; mean-square error performance; narrowband interference; nonWiener effect; nonlinear effect; transfer-function-based approach; Adaptive equalizers; Additive noise; Algorithm design and analysis; Approximation algorithms; Intersymbol interference; Least squares approximation; Narrowband; Numerical simulation; Steady-state; Wiener filter; Adaptive equalization; adaptive equalization; least mean squares algorithm; least mean-squares algorithm; steady-state analysis;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2008.928502
