Digital Predistortion Using Lookup Tables With Linear Interpolation and Extrapolation: Direct Least Squares Coefficient Adaptation

摘要

In this paper, we present a method to implement digital predistortion (DPD) memory models using lookup tables (LUTs) with linear interpolation and extrapolation. We introduce the required set of basis functions to describe this model. The DPD output is expressed as a linear combination of these basis functions and we show how to directly estimate the LUT entries using least squares. We show how this model achieves lower complexity at similar or better performance compared to polynomial models translated to LUTs with interpolation or models based on LUTs without interpolation whose coefficients are adapted directly. We refer to this model as the direct adaptation of LUTs with interpolation/extrapolation (DLUTI). In this paper we also introduce the composite memory polynomial model: a new polynomial model which is a hybrid between the generalized memory polynomial and the dynamic deviation reduction models. This model is used as a starting point to generate the final LUT-based model.