activity
20142026
most citedKalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics

595 citations · 3.6k across the 131 of their papers we have counts for

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Showing 2020 · eess.SPShow all

7 papers · 2 filters

eess.SP2020★ 50 cited

Model-Based Deep Learning

Nir Shlezinger, Jay Whang, Yonina C. Eldar +1

Signal processing, communications, and control have traditionally relied on classical statistical modeling techniques. Such model-based methods utilize mathematical formulations th…

eess.SP2020★ 26 cited

BiLiMO: Bit-Limited MIMO Radar via Task-Based Quantization

Feng Xi, Nir Shlezinger, Yonina C. Eldar

Recent years have witnessed growing interest in reduced cost radar systems operating with low power. Multiple-input multiple-output (MIMO) radar technology is known to achieve high…

eess.SP2020★ 1 cited

eSampling: Energy Harvesting ADCs

Neha Jain, Nir Shlezinger, Bhawna Tiwari +4

Analog-to-digital converters (ADCs) allow physical signals to be processed using digital hardware. The power consumed in conversion grows with the sampling rate and quantization re…

eess.SP2020

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…

eess.SP2020★ 132 cited

Spatial Modulation for Joint Radar-Communications Systems: Design, Analysis, and Hardware Prototype

Dingyou Ma, Nir Shlezinger, Tianyao Huang +4

Dual-function radar-communications (DFRC) systems implement radar and communication functionalities on a single platform. Jointly designing these subsystems can lead to substantial…

eess.SP2020

Data-Driven Symbol Detection via Model-Based Machine Learning

Nariman Farsad, Nir Shlezinger, Andrea J. Goldsmith +1

The design of symbol detectors in digital communication systems has traditionally relied on statistical channel models that describe the relation between the transmitted symbols an…

eess.SP2020

DeepSIC: Deep Soft Interference Cancellation for Multiuser MIMO Detection

Nir Shlezinger, Rong Fu, Yonina C. Eldar

Digital receivers are required to recover the transmitted symbols from their observed channel output. In multiuser multiple-input multiple-output (MIMO) setups, where multiple symb…