Title :
Optimal design and adaptive implementation of power estimation using the Hammerstein model
Author :
Huang, Aiping ; Laakso, Timo I.
Author_Institution :
Lab. of Signal Process. & Comput. Technol., Helsinki Univ. of Technol., Espoo, Finland
Abstract :
Optimal power estimation problem is investigated in this paper. The method of optimizing the Hammerstein model is introduced for the power estimation of real-valued stationary signals. An adaptive algorithm for nonstationary signals is developed. These enable an effective and accurate estimation of the signal power transmitted in a noisy environment like a fading mobile channel
Keywords :
FIR filters; adaptive estimation; adaptive filters; fading; filtering theory; noise; parameter estimation; signal processing; Hammerstein model; adaptive algorithm; adaptive implementation; fading mobile channel; noisy environment; nonstationary signals; optimal design; power estimation; real-valued stationary signals; AWGN; Adaptive signal processing; Additive white noise; Filtering; Finite impulse response filter; Gaussian noise; Noise reduction; Nonlinear filters; Telecommunication computing; Working environment noise;
Conference_Titel :
Circuits and Systems, 1996., IEEE 39th Midwest symposium on
Conference_Location :
Ames, IA
Print_ISBN :
0-7803-3636-4
DOI :
10.1109/MWSCAS.1996.587816
