The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 05, 2019

Filed:

Feb. 10, 2015
Applicant:

Nokia Solutions and Networks Gmbh and Co. KG;

Inventors:

Christian Reichl, Hirschau, DE;

Shavantha Kularatna, Flower Mound, TX (US);

Rene Roeschke, Mammendorf, DE;

Bjoern Jelonnek, Ulm, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H03F 1/26 (2006.01); H03F 1/32 (2006.01); H03F 3/195 (2006.01); H03F 3/24 (2006.01); H04L 27/36 (2006.01); H03F 3/189 (2006.01);
U.S. Cl.
CPC ...
H03F 1/3247 (2013.01); H03F 1/3258 (2013.01); H03F 3/189 (2013.01); H03F 3/195 (2013.01); H03F 3/24 (2013.01); H04L 27/368 (2013.01); H03F 2201/3212 (2013.01); H03F 2201/3233 (2013.01);
Abstract

The present invention addresses method, apparatus and computer program product for stabilization of the direct learning algorithm for wideband signals. Thereby, a signal to be amplified is input to a pre-distorter provided for compensating for non-linearity of the power amplifier, and the pre-distorted output signal from the pre-distorter is forwarded to the power amplifier. Parameters of the pre-distorter are adapted based on an error between the linearized signal output from the power amplifier and the signal to be amplified using an adaptive direct learning algorithm, and the linear system of equations formed by the direct learning algorithm are solved using a conjugate gradient algorithm, wherein, once per direct learning algorithm adaptation, at least one of the initial residual and the initial direction of the conjugate gradient algorithm are set based on the result of the previous adaptation.


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