Publication detail

Direct Learning Architecture For Digital Predistortion with Real-Valued Feedback

KRÁL, J.

Original Title

Direct Learning Architecture For Digital Predistortion with Real-Valued Feedback

Type

conference paper

Language

English

Original Abstract

The power efficiency is a key parameter of modern comunication systems. Efficient nonlinear power amplifiers are linearised using digital predistorters. Conventional predistorters require two ADCs in the feedback. In this paper we have proposed a modification of the direct learning architecture using solely one ADC in the feedback and an RF mixer instead of a quadrature mixer. This allows us to minimise the system complexity and power consumtion and maximise the efficiency. The proposed architecture has been verified experimentally and compared to the conventional digital predistorters. We have shown that it can achieve same linearisation performance as the conventional architecture with two ADCs. Moreover the proposed method outperformed the conventional DPD with indirect learning architecture.

Keywords

digital predistortion, direct learning architecture, real-valued feedback

Authors

KRÁL, J.

Released

26. 4. 2018

Publisher

Brno University of Technology, Faculty of Electrical Engineering and Communication

Location

Brno, Czech Republic

ISBN

978-80-214-5614-3

Book

Proceedings of the 24th Conference STUDENT EEICT 2018

Pages from

332

Pages to

336

Pages count

5

BibTex

@inproceedings{BUT149715,
  author="Jan {Král}",
  title="Direct Learning Architecture For Digital Predistortion with Real-Valued Feedback",
  booktitle="Proceedings of the 24th Conference STUDENT EEICT 2018",
  year="2018",
  pages="332--336",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  address="Brno, Czech Republic",
  isbn="978-80-214-5614-3"
}