Efficient Signal Alignment Algorithm for Undersampling Digital Predistortion

Abstract

Undersampling is an effective way to reduce the cost of digital predistortion (DPD), but it poses challenges for signal alignment, especially for fractional delay alignment. In this letter, a Taylor expansion-based method for fractional delay approximation solution is proposed. To verify the proposed alignment algorithm, the basis manifold regularization (BMR) is introduced to ensure that the DPD can converge to a satisfactory performance even at an ultralow sampling rate. Simulations and experimental tests demonstrate that the proposed method not only has high alignment accuracy but also low complexity in comparison with traditional methods.