Investigation of Parameter Adaptation in RF Power Amplifier Behavioral Models
This work provides a flexible evaluation tool for researchers designing parameter adaptation algorithms for digital predistortion, but it is an incremental step toward real-time hardware implementation.
The paper develops a measurement setup framework for evaluating parameter adaptation algorithms in behavioral model-based digital predistortion for RF power amplifiers, enabling analysis of convergence speed, quantization noise sensitivity, and predistortion performance without requiring full feedback loops.
This paper presents an investigation into parameter adaptation in behavioral model--based digital predistortion for radio frequency power amplifiers. A novel measurement setup framework that emulates real--time adaptation in transmitters is developed that allows evaluation of different parameters, configurations and adaptation algorithms. This setup relieves the need for full feedback loops for parameter adaptation while providing the flexibility needed in the design process of parameter adaptation. Issues such as convergence speed, sensitivity to quantization noise in the feedback loop and predistortion performance are investigated for some different parameter update algorithms using the proposed measurement setup. The approach presented in this paper allows the possibility to analyze different aspects of digital predistortion adaptation algorithms, and is an important enabling step for further research on parameter adaptation before the real--time hardware is implemented for use.