Digital predistortion using direct learning with reduced bandwidth feedback

Author

Lei Ding ; Mujica, Fernando ; Zigang Yang

Author_Institution

Texas Instrum., Dallas, TX, USA

fYear

2013

fDate

2-7 June 2013

Firstpage

1

Lastpage

3

Abstract

Digital predistortion (DPD) is a popular approach for linearizing power amplifiers (PAs) in wireless base stations and improving system efficiency. The feedback path in a DPD system typically requires 5x signal bandwidth to accommodate the bandwidth expansion caused by the DPD and nonlinear PA. In this paper, we propose a new approach for adapting DPD parameters using direct learning and reduced bandwidth feedback. The new approach is capable of achieving near full-rate DPD performance and linearization bandwidth with significantly reduced feedback bandwidth. Measurement results on a Doherty PA achieved more than 20 dB corrections over 200 MHz bandwidth for a 2-carrier WCDMA signal spanning 40 MHz with only 81.92 MHz feedback bandwidth.

Keywords

code division multiple access; integrated circuit modelling; power amplifiers; Doherty PA; WCDMA; bandwidth 200 MHz; bandwidth 81.92 MHz; digital predistortion; direct learning; frequency 40 MHz; power amplifiers; reduced bandwidth feedback; wireless base stations; Adaptation models; Bandwidth; Computer architecture; Equations; Mathematical model; Predistortion; Training; digital predistortion; direct learning; memory polynomial; reduced bandwidth feedback; undersample;

fLanguage

English

Publisher

ieee

Conference_Titel

Microwave Symposium Digest (IMS), 2013 IEEE MTT-S International

Conference_Location

Seattle, WA

ISSN

0149-645X

Print_ISBN

978-1-4673-6177-4

Type

conf

DOI

10.1109/MWSYM.2013.6697388

Filename

6697388