Title :
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
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;
Conference_Titel :
Signal Processing, 1996., 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-2912-0
DOI :
10.1109/ICSIGP.1996.566976
