Decomposed Vector Combination-Based Low-Complexity Behavioral Model for Digital Predistortion of RF Transmitters

TL;DR: A novel DVC-based low-complexity behavioral model for digital predistortion of RF transmitters achieves high performance with low complexity.

Abstract: In this paper, we present a novel behavioral modeling technique based on decomposed vector combination (DVC) for digital predistortion (DPD) of RF Transmitters. The basis function of the proposed DVC model consists of a piecewise function-based magnitude term and a linear phase-combination-based phase term. The novel DVC basis functions are still linear-in-parameters and go beyond the classical Volterra series. Compared with classical DPD models, the DVC model has a theoretically more powerful modeling capability through a richer form of basis functions. A novel basis function multiplexing-based model search algorithm, DVC search (DVCS), consisting of two main operations: nonlinear extension and phase rotation, is also proposed in this paper. The DVCS not only solves the practical deployment problem of the DVC model but also balances the performance and hardware complexity of the model. Two different power amplifiers (PAs) are used for comparison experiments to verify the performance of the DVCS model. The results of the experimental tests have demonstrated that the DVCS model can achieve an excellent trade-off between linearization performance and hardware complexity.