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

Siqi Wang (1) , Morgan Roger (1, 2) , Caroline Lelandais-Perrault (1, 2)

1 GeePs - Laboratoire Génie électrique et électronique de Paris
2 CentraleSupélec

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.

Keywords: digital predistortion; information criterion; nonlinear distortion; Optimization; RF power amplifiers; Index Terms-Digital predistortion; non- linear distortion; opitmization

Domains: Engineering Sciences [physics]; Signal and Image processing; Engineering Sciences [physics]; Electronics; Engineering Sciences [physics]; Micro and nanotechnologies/Microelectronics

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. ⟨10.1109/NEWCAS44328.2019.8961300⟩. ⟨hal-02054960v2⟩