Nonlinear effects in LMS adaptive equalizers

Author

Reuter, Michael ; Zeidler, James R.

Author_Institution

Space & Naval Warfare Syst. Centre, San Diego, CA, USA

Volume

47

Issue

6

fYear

1999

fDate

6/1/1999 12:00:00 AM

Firstpage

1570

Lastpage

1579

Abstract

An adaptive transversal equalizer based on the least-mean-square (LMS) algorithm, operating in an environment with a temporally correlated interference, can exhibit better steady-state mean-square-error (MSE) performance than the corresponding Wiener filter. This phenomenon is a result of the nonlinear nature of the LMS algorithm and is obscured by traditional analysis approaches that utilize the independence assumption (current filter weight vector assumed to be statistically independent of the current data vector). To analyze this equalizer problem, we use a transfer function approach to develop approximate analytical expressions of the LMS MSE for sinusoidal and autoregressive interference processes. We demonstrate that the degree to which LMS may outperform the corresponding Wiener filter is dependent on system parameters such as signal-to-noise ratio (SNR), signal-to-interference ratio (SIR), equalizer length, and the step-size parameter

Keywords

Wiener filters; adaptive equalisers; adaptive filters; autoregressive processes; filtering theory; land mobile radio; least mean squares methods; radiofrequency interference; LMS adaptive equalizers; LMS algorithm; MSE performance; SIR; SNR; Wiener filter; adaptive transversal equalizer; approximate analytical expressions; autoregressive interference; data vector; equalizer length; filter weight vector; least-mean-square algorithm; mobile radio; nonlinear effects; signal-to-interference ratio; signal-to-noise ratio; sinusoidal interference; statistically independent vector; steady-state mean-square-error; step-size parameter; system parameters; temporally correlated interference; transfer function; Adaptive equalizers; Adaptive filters; Algorithm design and analysis; Bandwidth; Equations; Interference; Least squares approximation; Steady-state; Transfer functions; Wiener filter;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.765126

Filename

765126