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Optimal Segmentation for Piecewise RF Power Amplifier Models

Magesacher, Thomas LU ; Singerl, Peter and Mataln, Martin (2016) In IEEE Microwave and Wireless Components Letters 26(11). p.909-911
Abstract

Accurate modeling of an RF power amplifier and/or its inverse is the core element of every digital predistortion system. An interesting alternative to the family of classic polynomial models are piecewise models, which divide the magnitude range into segments and define gain/phase-distortion through complex-valued functions on a per-segment basis. Naturally, the question arises whether a well-chosen non-uniform segmentation outperforms straightforward uniform segmentation and whether the benefit outweighs the extra effort. This work has two contributions: First, the segmentation that is optimal in the least-squares sense is determined jointly with the model coefficients and its benefit in terms of linearization improvement is... (More)

Accurate modeling of an RF power amplifier and/or its inverse is the core element of every digital predistortion system. An interesting alternative to the family of classic polynomial models are piecewise models, which divide the magnitude range into segments and define gain/phase-distortion through complex-valued functions on a per-segment basis. Naturally, the question arises whether a well-chosen non-uniform segmentation outperforms straightforward uniform segmentation and whether the benefit outweighs the extra effort. This work has two contributions: First, the segmentation that is optimal in the least-squares sense is determined jointly with the model coefficients and its benefit in terms of linearization improvement is demonstrated through measurements on a Doherty power amplifier. Second, a reduced-complexity approach with negligible performance loss is proposed.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Digital predistortion (DPD), nonlinear least-squares, piecewise segmentation, power amplifier (PA), spline
in
IEEE Microwave and Wireless Components Letters
volume
26
issue
11
pages
3 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:84994317349
  • wos:000388215900018
ISSN
1531-1309
DOI
10.1109/LMWC.2016.2614974
language
English
LU publication?
yes
id
e4fcecbe-8b8a-4f3c-9ad4-e53f72fe7cb6
date added to LUP
2016-12-05 11:19:15
date last changed
2017-09-18 11:30:07
@article{e4fcecbe-8b8a-4f3c-9ad4-e53f72fe7cb6,
  abstract     = {<p>Accurate modeling of an RF power amplifier and/or its inverse is the core element of every digital predistortion system. An interesting alternative to the family of classic polynomial models are piecewise models, which divide the magnitude range into segments and define gain/phase-distortion through complex-valued functions on a per-segment basis. Naturally, the question arises whether a well-chosen non-uniform segmentation outperforms straightforward uniform segmentation and whether the benefit outweighs the extra effort. This work has two contributions: First, the segmentation that is optimal in the least-squares sense is determined jointly with the model coefficients and its benefit in terms of linearization improvement is demonstrated through measurements on a Doherty power amplifier. Second, a reduced-complexity approach with negligible performance loss is proposed.</p>},
  articleno    = {7726033},
  author       = {Magesacher, Thomas and Singerl, Peter and Mataln, Martin},
  issn         = {1531-1309},
  keyword      = {Digital predistortion (DPD),nonlinear least-squares,piecewise segmentation,power amplifier (PA),spline},
  language     = {eng},
  month        = {11},
  number       = {11},
  pages        = {909--911},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  series       = {IEEE Microwave and Wireless Components Letters},
  title        = {Optimal Segmentation for Piecewise RF Power Amplifier Models},
  url          = {http://dx.doi.org/10.1109/LMWC.2016.2614974},
  volume       = {26},
  year         = {2016},
}