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  5. Sampling Rate Reduction for Digital Predistortion of Broadband RF Power Amplifiers
 
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Sampling Rate Reduction for Digital Predistortion of Broadband RF Power Amplifiers

Author(s)
Li, Yue  
Wang, Xiaoyu  
Zhu, Anding  
Uri
http://hdl.handle.net/10197/11359
Date Issued
2020-03
Date Available
2020-04-30T14:36:54Z
Abstract
In this article, we present a novel technique to build digital predistorters that can linearize broadband power amplifiers (PAs) using reduced sampling rates. In contrast to conventional digital predistortion (DPD) where oversampling is necessary to avoid aliasing effect, the proposed method cancels the aliasing distortion using a sliced multistage cancellation scheme. A large reduction of sampling rate can be achieved in digital implementation of DPD, significantly reducing power consumption and implementation cost. Experimental results show that a DPD with a sampling rate of merely 1.5x, instead of 5x, signal bandwidth, can still produce satisfactory performance within the linearization bandwidth but consume only one-third of power, compared with that using the conventional approaches. The proposed technique provides a promising solution for the next-generation 5G systems, where large signal bandwidths are required.
Sponsorship
Science Foundation Ireland
Type of Material
Journal Article
Publisher
IEEE
Journal
IEEE Transactions on Microwave Theory and Techniques
Volume
68
Issue
3
Start Page
1054
End Page
1064
Copyright (Published Version)
2019 IEEE
Subjects

Bandwidth

Nonlinear distortion

Power demand

Predistortion

Broadband communicati...

Clocks

DOI
10.1109/tmtt.2019.2944813
Language
English
Status of Item
Peer reviewed
ISSN
0018-9480
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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Sampling Rate Reduction_DPD.pdf

Size

2.39 MB

Format

Adobe PDF

Checksum (MD5)

2c0411cf080c6bb097c6e54e87f20a35

Owning collection
Electrical and Electronic Engineering Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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