On-line adaptive estimation of symbol period

Author

Doroslovaeki, M. ; Yao, Lei

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., George Washington Univ., Washington, DC, USA

Volume

3

fYear

1997

fDate

2-5 Nov 1997

Firstpage

1117

Abstract

The application of the least-mean-square (LMS) and recursive-least-square (RLS) algorithms to the estimation of symbol period is discussed. The algorithms are based on the measurement of the time between two consecutive detected transitions in noisy waveforms. Two versions of the algorithm are developed for white and colored measurement noise models. Conditions are derived that guarantee proper behavior, i.e. the convergence, of the LMS and RLS algorithms. Simulation results show the convergence of algorithms and compare the algorithms with respect to convergence speed

Keywords

adaptive estimation; convergence of numerical methods; least mean squares methods; recursive estimation; signal detection; white noise; LMS algorithm; RLS algorithm; colored noise; convergence speed; digitally modulated waveform detection; least-mean-square; measurement noise model; noisy waveforms; on-line adaptive estimation; recursive-least-square; simulation results; symbol period; time measurement; white noise; Adaptive estimation; Autocorrelation; Colored noise; Computer aided software engineering; Integrated circuit noise; Mean square error methods; Noise measurement; Random sequences; Stochastic resonance; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

MILCOM 97 Proceedings

Conference_Location

Monterey, CA

Print_ISBN

0-7803-4249-6

Type

conf

DOI

10.1109/MILCOM.1997.644873

Filename

644873