research
∙
09/18/2023
Outlier-Insensitive Kalman Filtering: Theory and Applications
State estimation of dynamical systems from noisy observations is a funda...
share
research
∙
09/10/2023
Deep Learning-Aided Subspace-Based DOA Recovery for Sparse Arrays
Sparse arrays enable resolving more direction of arrivals (DoAs) than an...
research
∙
07/10/2023
Joint Communications and Sensing Hybrid Beamforming Design via Deep Unfolding
Joint communications and sensing (JCAS) is envisioned as a key feature i...
research
∙
06/24/2023
Joint Communications and Sensing Design for Multi-Carrier MIMO Systems
In conventional joint communications and sensing (JCAS) designs for mult...
research
∙
06/04/2023
SubspaceNet: Deep Learning-Aided Subspace Methods for DoA Estimation
Direction of arrival (DoA) estimation is a fundamental task in array pro...
research
∙
05/12/2023
Adaptive and Flexible Model-Based AI for Deep Receivers in Dynamic Channels
Artificial intelligence (AI) is envisioned to play a key role in future ...
research
∙
03/03/2023
AI-Empowered Hybrid MIMO Beamforming
Hybrid multiple-input multiple-output (MIMO) is an attractive technology...
research
∙
02/23/2023
Deep Unfolding Hybrid Beamforming Designs for THz Massive MIMO Systems
Hybrid beamforming (HBF) is a key enabler for wideband terahertz (THz) m...
research
∙
02/10/2023
On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels
We analytically derive from first physical principles the functional dep...
research
∙
02/05/2023
Modular Model-Based Bayesian Learning for Uncertainty-Aware and Reliable Deep MIMO Receivers
In the design of wireless receivers, DNNs can be combined with tradition...
research
∙
01/15/2023
CRC-Aided Learned Ensembles of Belief-Propagation Polar Decoders
Polar codes have promising error-correction capabilities. Yet, decoding ...
research
∙
10/23/2022
LQGNet: Hybrid Model-Based and Data-Driven Linear Quadratic Stochastic Control
Stochastic control deals with finding an optimal control signal for a dy...
research
∙
10/18/2022
Split-KalmanNet: A Robust Model-Based Deep Learning Approach for SLAM
Simultaneous localization and mapping (SLAM) is a method that constructs...
research
∙
10/12/2022
Outlier-Insensitive Kalman Filtering Using NUV Priors
The Kalman filter (KF) is a widely-used algorithm for tracking the laten...
research
∙
09/03/2022
Data Augmentation for Deep Receivers
Deep neural networks (DNNs) allow digital receivers to learn to operate ...
research
∙
08/23/2022
Joint Privacy Enhancement and Quantization in Federated Learning
Federated learning (FL) is an emerging paradigm for training machine lea...
research
∙
07/29/2022
Deep Learning Based Successive Interference Cancellation for the Non-Orthogonal Downlink
Non-orthogonal communications are expected to play a key role in future ...
research
∙
06/24/2022
Deep-Learning-Aided Distributed Clock Synchronization for Wireless Networks
The proliferation of wireless communications networks over the past deca...
research
∙
06/09/2022
Discriminative and Generative Learning for Linear Estimation of Random Signals [Lecture Notes]
Inference tasks in signal processing are often characterized by the avai...
research
∙
06/08/2022
Channel Estimation with Hybrid Reconfigurable Intelligent Metasurfaces
Reconfigurable Intelligent Surfaces (RISs) are envisioned to play a key ...
research
∙
06/07/2022
Decentralized Low-Latency Collaborative Inference via Ensembles on the Edge
The success of deep neural networks (DNNs) is heavily dependent on compu...
research
∙
05/05/2022
Model-Based Deep Learning: On the Intersection of Deep Learning and Optimization
Decision making algorithms are used in a multitude of different applicat...
research
∙
03/27/2022
Online Meta-Learning For Hybrid Model-Based Deep Receivers
Recent years have witnessed growing interest in the application of deep ...
research
∙
02/21/2022
Composite Anomaly Detection via Hierarchical Dynamic Search
Anomaly detection among a large number of processes arises in many appli...
research
∙
02/16/2022
Deep-Learning-Assisted Configuration of Reconfigurable Intelligent Surfaces in Dynamic rich-scattering Environments
The integration of Reconfigurable Intelligent Surfaces (RISs) into wirel...
research
∙
02/10/2022
On the Acquisition of Stationary Signals Using Uniform ADCs
In this work, we consider the acquisition of stationary signals using un...
research
∙
02/06/2022
PhysFad: Physics-Based End-to-End Channel Modeling of RIS-Parametrized Environments with Adjustable Fading
Programmable radio environments parametrized by reconfigurable intellige...
research
∙
02/04/2022
Wideband Multi-User MIMO Communications with Frequency Selective RISs: Element Response Modeling and Sum-Rate Maximization
Reconfigurable Intelligent Surfaces (RISs) are an emerging technology fo...
research
∙
10/28/2021
DeepNP: Deep Learning-Based Noise Prediction for Ultra-Reliable Low-Latency Communications
Closing the gap between high data rates and low delay in real-time strea...
research
∙
10/18/2021
Unsupervised Learned Kalman Filtering
In this paper we adapt KalmanNet, which is a recently pro-posed deep neu...
research
∙
10/10/2021
Uncertainty in Data-Driven Kalman Filtering for Partially Known State-Space Models
Providing a metric of uncertainty alongside a state estimate is often cr...
research
∙
09/22/2021
Deep Augmented MUSIC Algorithm for Data-Driven DoA Estimation
Direction of arrival (DoA) estimation is a crucial task in sensor array ...
research
∙
07/21/2021
KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics
Real-time state estimation of dynamical systems is a fundamental task in...
research
∙
04/10/2021
Hybrid Reconfigurable Intelligent Metasurfaces: Enabling Simultaneous Tunable Reflections and Sensing for 6G Wireless Communications
Current discussions on the sixth Generation (6G) of wireless communicati...
research
∙
03/31/2021
Federated Learning: A Signal Processing Perspective
The dramatic success of deep learning is largely due to the availability...
research
∙
03/24/2021
Meta-ViterbiNet: Online Meta-Learned Viterbi Equalization for Non-Stationary Channels
Deep neural networks (DNNs) based digital receivers can potentially oper...
research
∙
03/08/2021
Reconfigurable Intelligent Surfaces for Rich Scattering Wireless Communications: Recent Experiments, Challenges, and Opportunities
Recent advances in the fabrication and experimentation of Reconfigurable...
research
∙
02/05/2021
LoRD-Net: Unfolded Deep Detection Network with Low-Resolution Receivers
The need to recover high-dimensional signals from their noisy low-resolu...
research
∙
01/12/2021
Model-Based Machine Learning for Communications
We present an introduction to model-based machine learning for communica...
research
∙
12/15/2020
Model-Based Deep Learning
Signal processing, communications, and control have traditionally relied...
research
∙
11/14/2020
FedRec: Federated Learning of Universal Receivers over Fading Channels
Wireless communications are often subject to fading conditions. Various ...
research
∙
10/12/2020
Multi-Level Group Testing with Application to One-Shot Pooled COVID-19 Tests
One of the main challenges in containing the Coronoavirus disease 2019 (...
research
∙
09/29/2020
Task-Based Analog-to-Digital Converters
Obtaining digital representations of multivariate continuous-time (CT) s...
research
∙
09/27/2020
Over-the-Air Federated Learning from Heterogeneous Data
Federated learning (FL) is a framework for distributed learning of centr...
research
∙
07/16/2020
eSampling: Energy Harvesting ADCs
Analog-to-digital converters (ADCs) allow physical signals to be process...
research
∙
06/14/2020
Dynamic Metasurface Antennas for 6G Extreme Massive MIMO Communications
Next generation wireless base stations and access points will transmit a...
research
∙
06/05/2020
UVeQFed: Universal Vector Quantization for Federated Learning
Traditional deep learning models are trained at a centralized server usi...
research
∙
06/05/2020
Inference from Stationary Time Sequences via Learned Factor Graphs
The design of methods for inference from time sequences has traditionall...
research
∙
02/29/2020
The Rate Distortion Function of Asynchronously Sampled Memoryless Cyclostationary Gaussian Processes
Man-made communications signals are typically modelled as continuous-tim...
research
∙
02/14/2020