36 citations · 96 across the 10 of their papers we have counts for
3 papers · 1 filter
DPD-NeuralEngine: A 22-nm 6.6-TOPS/W/mm Recurrent Neural Network Accelerator for Wideband Power Amplifier Digital Pre-Distortion
Ang Li, Haolin Wu, Yizhuo Wu +3
The increasing adoption of Deep Neural Network (DNN)-based Digital Pre-distortion (DPD) in modern communication systems necessitates efficient hardware implementations. This paper…
MP-DPD: Low-Complexity Mixed-Precision Neural Networks for Energy-Efficient Digital Predistortion of Wideband Power Amplifiers
Yizhuo Wu, Ang Li, Mohammadreza Beikmirza +5
Digital Pre-Distortion (DPD) enhances signal quality in wideband RF power amplifiers (PAs). As signal bandwidths expand in modern radio systems, DPD's energy consumption increasing…
OpenDPD: An Open-Source End-to-End Learning & Benchmarking Framework for Wideband Power Amplifier Modeling and Digital Pre-Distortion
Yizhuo Wu, Gagan Deep Singh, Mohammadreza Beikmirza +3
With the rise in communication capacity, deep neural networks (DNN) for digital pre-distortion (DPD) to correct non-linearity in wideband power amplifiers (PAs) have become promine…