36 citations · 96 across the 10 of their papers we have counts for
10 papers
BitFair: A 12-nm Bit-Serial CNN Accelerator with Learnable Early Termination and Adaptive Bit Ordering for Ultra-Low-Power XR Vision
Ang Li, Chang Gao
Extended Reality (XR) wearables require always-on perception within tight power envelopes of a few watts and motion-to-photon latency budgets below 20 ms, leaving only a few millis…
Neural-HAR: A Dimension-Gated CNN Accelerator for Real-Time Radar Human Activity Recognition
Yizhuo Wu, Francesco Fioranelli, Chang Gao
Radar-based human activity recognition (HAR) is attractive for unobtrusive and privacy-preserving monitoring, yet many CNN/RNN solutions remain too heavy for edge deployment, and e…
OpenDPDv2: A Unified Learning and Optimization Framework for Neural Network Digital Predistortion
Yizhuo Wu, Ang Li, Chang Gao
Neural network (NN)-based Digital Predistortion (DPD) improves linearization for wideband radio frequency (RF) power amplifiers (PAs) but often increases the complexity of the digi…
SparseDPD: A Sparse Neural Network-based Digital Predistortion FPGA Accelerator for RF Power Amplifier Linearization
Manno Versluis, Yizhuo Wu, Chang Gao
Digital predistortion (DPD) is crucial for linearizing radio frequency (RF) power amplifiers (PAs), improving signal integrity and efficiency in wireless systems. Neural network (N…
TCN-DPD: Parameter-Efficient Temporal Convolutional Networks for Wideband Digital Predistortion
Huanqiang Duan, Manno Versluis, Qinyu Chen +2
Digital predistortion (DPD) is essential for mitigating nonlinearity in RF power amplifiers, particularly for wideband applications. This paper presents TCN-DPD, a parameter-effici…
DeltaDPD: Exploiting Dynamic Temporal Sparsity in Recurrent Neural Networks for Energy-Efficient Wideband Digital Predistortion
Yizhuo Wu, Yi Zhu, Kun Qian +5
Digital Predistortion (DPD) is a popular technique to enhance signal quality in wideband RF power amplifiers (PAs). With increasing bandwidth and data rates, DPD faces significant…
RadMamba: Efficient Human Activity Recognition through Radar-based Micro-Doppler-Oriented Mamba State-Space Model
Yizhuo Wu, Francesco Fioranelli, Chang Gao
Radar-based Human Activity Recognition (HAR) is an attractive alternative to wearables and cameras because it preserves privacy, and is contactless and robust to occlusions. Howeve…
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…