Wideband digital predistortion with sub-Nyquist nonuniform sampling and reconstruction of feedback path

Götthans, Tomáš; Mars̆álek, Roman; Gotthans, Jakub

doi:10.1109/pawr.2017.7875576

Cited by 1 publication

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [17], authors have given the Volterra series with polyphase representations at lower sampling rate. This technique has been used in [18] for DPD identification to reduce the sampling rate of the feedback path. In [19], the PNS technique was used to reconstruct a wide-band signal and a band-limited DPD based on polyphase technique has been proposed.…”

Section: Introductionmentioning

confidence: 99%

A Digital Predistortion for Concurrent Dual-Band Power Amplifier Linearization Based on Periodically Nonuniform Sampling Theory

Wang

Cao

Hou

et al. 2022

IEEE Trans. Microwave Theory Techn.

View full text Add to dashboard Cite

In this paper, we propose a novel technique of digital predistortion (DPD) for dual-band power amplifiers (PA) based on periodically nonuniform sampling (PNS) theory. In contrast to conventional 2D-DPD models, the proposed PNS-DPD has only a single input which can largely reduce the model complexity. We fold the two stimuli with aliasing and feed it to a simple single-band DPD model. The desired predistorted signals are reconstructed from aliased DPD output through the PNS theory. Compared with conventional multi-input models which include numerous intermodulation products of the input signals, the complexity of the proposed single-input PNS-DPD model is hugely decreased. The model coefficients of the proposed PNS-DPD can be easily extracted with conventional direct or indirect learning architecture. We experimentally evaluate the proposed DPD on a test bench and compare it with other DPD techniques in the literature. The implementation complexity can be reduced by over 30% and the identification complexity is also largely reduced.

show abstract

Section: Introductionmentioning

confidence: 99%