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Article Dans Une Revue IEEE Transactions on Microwave Theory and Techniques Année : 2022

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

Siqi Wang
Wenhui Cao
Rui Hou

Résumé

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.
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Dates et versions

hal-03783563 , version 1 (22-09-2022)

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Siqi Wang, Wenhui Cao, Rui Hou, Thomas Eriksson. A Digital Predistortion for Concurrent Dual-Band Power Amplifier Linearization Based on Periodically Nonuniform Sampling Theory. IEEE Transactions on Microwave Theory and Techniques, 2022, 70 (1), pp.466-475. ⟨10.1109/TMTT.2021.3119340⟩. ⟨hal-03783563⟩
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