1.2k citations · 2.3k across the 77 of their papers we have counts for
10 papers · 2 filters
Bayesian Federated Learning over Wireless Networks
Seunghoon Lee, Chanho Park, Song-Nam Hong +2
Federated learning is a privacy-preserving and distributed training method using heterogeneous data sets stored at local devices. Federated learning over wireless networks requires…
Deep Networks for Direction-of-Arrival Estimation in Low SNR
Georgios K. Papageorgiou, Mathini Sellathurai, Yonina C. Eldar
In this work, we consider direction-of-arrival (DoA) estimation in the presence of extreme noise using Deep Learning (DL). In particular, we introduce a Convolutional Neural Networ…
Unfolding Neural Networks for Compressive Multichannel Blind Deconvolution
Bahareh Tolooshams, Satish Mulleti, Demba Ba +1
We propose a learned-structured unfolding neural network for the problem of compressive sparse multichannel blind-deconvolution. In this problem, each channel's measurements are gi…
Automotive Radar Interference Mitigation with Unfolded Robust PCA based on Residual Overcomplete Auto-Encoder Blocks
Nicolae-Cătălin Ristea, Andrei Anghel, Radu Tudor Ionescu +1
In autonomous driving, radar systems play an important role in detecting targets such as other vehicles on the road. Radars mounted on different cars can interfere with each other,…
Dynamic Metasurface Antennas for 6G Extreme Massive MIMO Communications
Nir Shlezinger, George C. Alexandropoulos, Mohammadreza F. Imani +2
Next generation wireless base stations and access points will transmit and receive using extremely massive numbers of antennas. A promising technology for realizing such massive ar…
Ensemble Wrapper Subsampling for Deep Modulation Classification
Sharan Ramjee, Shengtai Ju, Diyu Yang +3
Subsampling of received wireless signals is important for relaxing hardware requirements as well as the computational cost of signal processing algorithms that rely on the output s…