New Preprint Available. Neural Networks are taking over DPD!

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.

My Talk at DSP50

I recently spoke at Rice’s DSP50 Event. This was a major event that celebrated 50 years of DSP at Rice. The slide deck can be found here.