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Optimization of a pruned 2-D Digital Predistortion Model Structure for Power Amplifiers Linearization

Abstract : Two-dimensional digital predistortion (2-D DPD) is one of the most commonly used approaches to linearize the concurrent dual-band radio frequency (RF) power amplifiers (PA). This paper explores the use of a hill-climbing optimization heuristic to determine the optimal structure for 2-D DPD. To improve convergence and reduce computation time, we propose a new parameterization for the 2-D DPD model. The proposed search criterion is based on the generalized information criterion, which represents the trade-off between the DPD linearization accuracy in both bands and the model complexity. A comparison against a compressed-sensing-based method is also made. The effectiveness of the proposed method is validated with two 20~MHz long-term-evolution (LTE) signals on two carriers with 100~MHz frequency separation.
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https://hal-centralesupelec.archives-ouvertes.fr/hal-02054960
Contributor : Morgan Roger <>
Submitted on : Friday, December 6, 2019 - 4:49:25 PM
Last modification on : Wednesday, September 16, 2020 - 5:51:56 PM
Long-term archiving on: : Saturday, March 7, 2020 - 5:27:59 PM

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  • HAL Id : hal-02054960, version 2

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Siqi Wang, Morgan Roger, Caroline Lelandais-Perrault. Optimization of a pruned 2-D Digital Predistortion Model Structure for Power Amplifiers Linearization. NEWCAS 2019 17th IEEE International New Circuits and Systems Conference, Jun 2019, Munich, Germany. ⟨hal-02054960v2⟩

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