Welcome to Research Repository UCD
Research Repository UCD is a digital collection of open access scholarly research publications from University College Dublin. Research Repository UCD collects, preserves and makes freely available publications including peer-reviewed articles, working papers and conference papers created by UCD researchers. Where material has already been published it is made available subject to the open-access policies of the original publishers. This service is maintained by UCD Library.
Low Complexity Stochastic Optimization-Based Model Extraction for Digital Predistortion of RF Power Amplifiers
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| TMTT-2015-10-1375R1_completemanuscript.pdf | 5.2 MB | Adobe PDF | Download |
| Title: | Low Complexity Stochastic Optimization-Based Model Extraction for Digital Predistortion of RF Power Amplifiers | Authors: | Kelly, Noel Zhu, Anding |
Permanent link: | http://hdl.handle.net/10197/8389 | Date: | May-2016 | Online since: | 2017-03-10T15:42:03Z | Abstract: | This paper introduces a low-complexity stochastic optimization-based model coefficients extraction solution for digital predistortion of RF power amplifiers (PAs). The proposed approach uses a closed-loop extraction architecture and replaces conventional least squares (LS) training with a modified version of the simultaneous perturbation stochastic approximation (SPSA) algorithm that requires a very low number of numerical operations per iteration, leading to considerable reduction in hardware implementation complexity. Experimental results show that the complete closed-loop stochastic optimization-based coefficient extraction solution achieves excellent linearization accuracy while avoiding the complex matrix operations associated with conventional LS techniques. | Funding Details: | European Commission - European Regional Development Fund Science Foundation Ireland |
Type of material: | Journal Article | Publisher: | IEEE | Journal: | IEEE Transactions on Microwave Theory and Techniques | Volume: | 64 | Issue: | 5 | Start page: | 1373 | End page: | 1382 | Copyright (published version): | 2016 IEEE | Keywords: | Digital predistortion; Linearization; Model extraction; Stochastic optimization; Simultaneous perturbation stochastic approximation; Power amplifier | DOI: | 10.1109/TMTT.2016.2547383 | Language: | en | Status of Item: | Peer reviewed |
| Appears in Collections: | Electrical and Electronic Engineering Research Collection |
Show full item record
SCOPUSTM
Citations
50
4
Last Week
0
0
Last month
checked on Feb 12, 2019
Download(s) 50
90
checked on May 25, 2018
Google ScholarTM
Check
Altmetric
This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.