Exploring predistortion training algorithms in a Cartesian feedback-trained digital predistortion system for RF power amplifier linearization
Name
79651109-MIT.pdf
Description
Full printable version
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6.05 MB
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Checksum (MD5)
55bb57b8e09aac72fc8b364a22c2543b
Author(s)
Huang, Jeffrey B
Advisor(s)
Joel L. Dawson.
Date Issued
2006
Publisher
Massachusetts Institute of Technology
Abstract
A Cartesian feedback-trained digital predistortion system for RF power amplifier linearization offers many advantages with its combination of two different linearization techniques. This thesis describes such a system, focusing on the important issue of predistorter training. It examines and analyzes in great detail the promising loop filter pre-charging optimization and the tradeoffs associated with such training, developing a model that provides many valuable system design insights. In order establish a means to experimentally verify the theory and explore predistortion training algorithms, this thesis presents the design, development, and characterization of a mock-up prototype that models the essential features of the actual Cartesian feedback-trained digital predistortion system. The mock-up serves as a standalone proof-of-concept system that demonstrates the benefits and tradeoffs of loop filter pre-charging in predistorter training. It confirms the theory while also revealing practical issues pertaining to the limits on performance.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
Includes bibliographical references (p. 117-118).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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