Optimal linear filtering for power estimation of slowly-varying complex-valued signals

Author

Aiping Huang ; Laakso, Timo I. ; Ovaska, Seppo J. ; Hartimo, Iiro O.

Author_Institution

Lab. of Signal Process. & Comput. Technol., Helsinki Univ. of Technol., Espoo, Finland

Volume

1

fYear

1996

Firstpage

76

Abstract

A novel method for designing the FIR filter in the Hammerstein model for power estimation of complex-valued signals is proposed. This enables a computationally effective optimal power estimation with a prescribed delay in minimum mean squared error sense, a great reduction of the estimation bias which is inherent in power estimation. Illustrations are given by assuming a constant input signal add a Rayleigh distributed input fading signal, respectively, both signals are complex-valued and corrupted by Gaussian noise

Keywords

FIR filters; Gaussian noise; circuit optimisation; delays; digital filters; fading; filtering theory; parameter estimation; prediction theory; probability; FIR filter design; Gaussian noise; Hammerstein model; Rayleigh distributed input fading signal; constant input signal; delay; estimation bias reduction; minimum mean squared error; optimal linear filtering; optimal power estimation; slowly varying complex valued signals; Additive white noise; Delay estimation; Finite impulse response filter; Gaussian noise; Maximum likelihood detection; Mobile communication; Nonlinear filters; Signal design; Signal processing; Telecommunication computing;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 1996., 3rd International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-2912-0

Type

conf

DOI

10.1109/ICSIGP.1996.566976

Filename

566976