Title :
A modified RLS algorithm for identification of power amplifier nonlinear model
Author :
Li, You ; Zhang, Xiaolin
Author_Institution :
Sch. of Electron. & Inf. Eng., Beihang Univ. Beijing, Beijing, China
Abstract :
Identifying accurately the parameters of power amplifier (PA) nonlinear model is essential in modeling and predistortion of PA. RLS (Recursive Least Square) is a common used algorithm in parameter identification. The proposed algorithm modifies the cost function of the conventional RLS by multiplying a weighting function. The simulation results verify that the modified algorithm has better normalized mean square error (NMSE) performance than the conventional RLS.
Keywords :
mean square error methods; parameter estimation; power amplifiers; recursive estimation; NMSE performance; cost function; modified RLS algorithm; normalized mean square error performance; parameter identification; power amplifier nonlinear model; recursive least square; weighting function; PA; RLS; identification; modeling; nonlinear;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1586-0
DOI :
10.1109/ICCSNT.2011.6182435
