Complexity Optimized Digital Predistortion Model of RF Power Amplifiers

A novel behavioral modeling technique for digital predistortion of radio frequency power amplifiers (PAs) is proposed. The proposed basis-propagating selection (BAPS) model has an advantage on complexity since its basis functions are constructed as delay or a combination of existing basis functions. The BAPS model effectively optimizes the running time complexity while maintaining the generality of a full Volterra series. A greedy search procedure is applied to select the optimal basis functions. Compared with truncated Volterra models and pruned models obtained by popular pruning techniques, the superior performance of the BAPS model, in terms of accuracy and identification stability, has been fairly justified. The linearization measurements on different types of PAs illustrate that the BAPS model can robustly outperform other models from literature while achieving a low running complexity.