Complexity-Optimized Adaptive Model for Multiband Digital Predistortion of RF Power Amplifiers

In this article, we present a low-complexity adaptive digital predistortion (DPD) model for concurrent multiband (MB) power amplifiers (PAs). A novel MB basis function space is constructed for the proposed MB vector combination search (MB-VCS) model by performing multidimensional extensions and adding piecewise linear functions to the Polar Volterra series. The proposed basis function multiplexing-based model search algorithm also helps the MB-VCS model to balance model performance and complexity. The MB-VCS model contains novel in-band and cross-band terms to characterize complex interactions between different band signals and can adaptively construct intermodulation (IMD) terms to handle arbitrary carrier configurations. In order to further exploit the advantages of the MB-VCS model, the MB piecewise VCS (MB-PVCS) model with MB-VCS as a submodel based on the piecewise modeling technique is proposed in this article, and an efficient classification controller construction strategy is designed for the MB-PVCS model. The experimental test results confirm that the MB-VCS and MB-PVCS models achieve a better performance-complexity tradeoff than the state-of-the-art MB single and MB piecewise models.