RFWebLab

I released a new verison of my DPD library for Matlab yesterday. You can find the source code here. This software can enable you to easily add DPD to any of your Matlab based wireless prototyping. This new version now supports the Generalized Memory Polynomial (GMP). This is a more expressive model than the standard memory polynomial. The extra memory effects captured in this model are especially helpful for signals with larger bandwidth such as what we see in 5G NR.

I have a new preprint available for my submission to the 2019 IEEE International Workshop on Signal Processing Systems in Nanjing, China. The paper is titled “Design and Implementation of a Neural Network Based Predistorter for Enhanced Mobile Broadband” and is available here. In this paper, I use a neural network (NN) to implement digital predistortion (DPD) to correct for power amplifier (PA) nonlinearities. The main contributions are: A novel training method where we learn the NN DPD by first modeling the PA with a NN and backpropagating through the PA NN model to update the DPD NN weights.