Digital Predistortion of an RF Power Amplifier Using a Reduced Volterra Series Model With a Memory Polynomial Estimator

A technique for reducing the number of basis waveforms used in a Volterra series model for digital predistortion (DPD) of radio frequency power amplifiers is proposed. An effective delay is defined for each basis waveform. The DPD model is constrained so that the basis waveforms used have unique del...

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Bibliographic Details
Published in:IEEE transactions on microwave theory and techniques 2017-10, Vol.65 (10), p.3613-3623
Main Author: Braithwaite, R. N.
Format: Article
Language:English
Subjects:
Closed-loop estimation
Delay
Delays
digital predistortion (DPD)
Electronics
Estimation
Fast Fourier transformations
Fourier transforms
Frequency-domain analysis
Indexes
Notch filters
OFDM
Polynomials
Power amplifiers
Pruning
Radio frequency
Radio transmitters
Regularization
Waveforms
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Summary:A technique for reducing the number of basis waveforms used in a Volterra series model for digital predistortion (DPD) of radio frequency power amplifiers is proposed. An effective delay is defined for each basis waveform. The DPD model is constrained so that the basis waveforms used have unique delays. When several of the original Volterra terms have a common delay, they are either grouped together to form a single basis waveform or pruned to discard all but the dominant term. It is shown that grouping and pruning produce similar ACLR results when the coefficient estimator notch filters the linear signal bandwidth and applies regularization. Unique delay DPD basis sets are compatible with a fractionally sampled memory polynomial estimator. The basis waveforms within the estimator are specified in the frequency domain as a function of memoryless waveforms and delay operators, thereby reducing the number of fast Fourier transforms needed and allowing for fractional tap spacing that matches the effective delays of Volterra basis waveforms used within the DPD basis set. The approximation associated with using a memory polynomial estimator is sufficiently accurate for a closed-loop estimator to converge to a desired steady state.
ISSN:0018-9480
1557-9670
DOI:10.1109/TMTT.2017.2729513