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Discontinuity Characterization and Low-Complexity Smoothing in RF-PA Polynomial Piecewise Modeling
Carolina Pedrosa1,2, Dang-Kièn Germain Pham1, Peter Rashev3
1Laboratoire Traitement et Communication de l'Information (LTCI), Télécom Paris, Institut Polytechnique de Paris, 91120 Palaiseau, France.
Sensors (Basel, Switzerland)
|November 13, 2025
Summary
This study introduces a novel post-processing technique to smooth discontinuities in piecewise power amplifier (PA) models. This method enhances digital predistortion (DPD) performance by improving prediction accuracy for PA nonlinearities.
Area of Science:
- Electrical Engineering
- Signal Processing
- Nonlinear Systems
Background:
- Piecewise modeling of power amplifiers (PAs) uses polynomial segments to represent nonlinear behavior.
- Recombining these segments can cause discontinuities, reducing prediction accuracy and digital predistortion (DPD) performance.
Purpose of the Study:
- To develop a statistical framework for detecting discontinuities in PA models.
- To propose a low-complexity smoothing technique to mitigate these discontinuities and improve DPD.
Main Methods:
- Statistical detection of discontinuities via localized variations in amplitude and phase responses.
- Application of a raised cosine weighting function for post-processing smoothing at model transition regions.
- Case study using the Vector-Switched Generalized Memory Polynomial (VS-GMP) model.
Main Results:
- Consistent improvements in PA modeling accuracy across Doherty and Single-Stage architectures.
- Up to a 3 dB reduction in Normalized Mean Squared Error (NMSE).
- Significant suppression of spectral errors for 5G/LTE signals.
Conclusions:
- The proposed smoothing technique effectively addresses discontinuities in piecewise PA models without retraining.
- The method seamlessly integrates as a post-processing tool, enhancing DPD performance.
- Validated for various 5G/LTE signals and PA types, demonstrating broad applicability.
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