DocumentCode
3411891
Title
A novel reduced order RLS predistortion
Author
Niu, Wei ; Wang, Minxi ; Chen, Kaya
Author_Institution
Dept. of Electromagn. & Microwave, SouthWest Jiao tong Univ., Chengdu, China
Volume
4
fYear
2005
fDate
4-7 Dec. 2005
Abstract
In this paper, a new structure of predistorter, which composed of a rational function and polynomial function, is presented for solving the nonlinear distortion of power amplifier. Amplitude predistorter is implemented by rational function and phase predistorter polynomial function. First, the rational function is transformed into polynomial function structure. Thus, the basic idea of the reduced order RLS based polynomial predistortion algorithm is used, system structure is same to original, only the algorithm of adaptation process is modified to approximate the target function with two simpler functions. A complex function is decomposed into two simpler functions so that we can compute the RLS algorithm with much less complexity. Using reduced order RLS algorithm, the proposed structure of predistorter show superior performance compared to the conventional RLS rational function predistortion with the same computational complexity or with the same number of coefficient.
Keywords
computational complexity; least squares approximations; network analysis; nonlinear distortion; polynomials; power amplifiers; rational functions; reduced order systems; amplitude predistorter; computational complexity; nonlinear distortion; phase predistorter; polynomial function; polynomial predistortion algorithm; power amplifiers; rational function; reduced order RLS predistortion; Amplitude modulation; Computational complexity; Microwave amplifiers; Nonlinear distortion; Phase modulation; Polynomials; Power amplifiers; Predistortion; Resonance light scattering; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Microwave Conference Proceedings, 2005. APMC 2005. Asia-Pacific Conference Proceedings
Print_ISBN
0-7803-9433-X
Type
conf
DOI
10.1109/APMC.2005.1606783
Filename
1606783
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