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09/15/2023
Channel Estimation in Underdetermined Systems Utilizing Variational Autoencoders
In this work, we propose to utilize a variational autoencoder (VAE) for ...
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07/11/2023
Leveraging Variational Autoencoders for Parameterized MMSE Channel Estimation
In this manuscript, we propose to utilize the generative neural network-...
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05/25/2023
Optimization and Interpretability of Graph Attention Networks for Small Sparse Graph Structures in Automotive Applications
For automotive applications, the Graph Attention Network (GAT) is a prom...
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05/22/2023
On Learning the Tail Quantiles of Driving Behavior Distributions via Quantile Regression and Flows
Towards safe autonomous driving (AD), we consider the problem of learnin...
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05/12/2023
A Multidimensional Graph Fourier Transformation Neural Network for Vehicle Trajectory Prediction
This work introduces the multidimensional Graph Fourier Transformation N...
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05/05/2023
Enhanced Low-Complexity FDD System Feedback with Variable Bit Lengths via Generative Modeling
Recently, a versatile limited feedback scheme based on a Gaussian mixtur...
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04/27/2023
A Versatile Low-Complexity Feedback Scheme for FDD Systems via Generative Modeling
In this work, we propose a versatile feedback scheme which can be deploy...
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04/21/2023
Gradient Derivation for Learnable Parameters in Graph Attention Networks
This work provides a comprehensive derivation of the parameter gradients...
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02/01/2023
Predicting CSI Sequences With Attention-Based Neural Networks
In this work, we consider the problem of multi-step channel prediction i...
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01/20/2023
Asymptotic Behavior of Zero-Forcing Precoding based on Imperfect Channel Knowledge for Massive MISO FDD Systems
In this work, we study the asymptotic behavior of the zero-forcing preco...
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01/16/2023
Learning a Gaussian Mixture Model from Imperfect Training Data for Robust Channel Estimation
In this letter, we propose a Gaussian mixture model (GMM)-based channel ...
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12/08/2022
On the Mean Square Error Optimal Estimator in One-Bit Quantized Systems
This paper investigates the mean square error (MSE)-optimal conditional ...
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10/31/2022
Variational Inference Aided Estimation of Time Varying Channels
One way to improve the estimation of time varying channels is to incorpo...
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10/27/2022
Model Order Selection with Variational Autoencoding
Classical methods for model order selection often fail in scenarios with...
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10/27/2022
High SNR Analysis of RIS aided MIMO BC Channels
We analyze the influence of an reconfigurable intelligent surface (RIS) ...
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07/28/2022
Evaluation of a Gaussian Mixture Model-based Channel Estimator using Measurement Data
In this work, we use real-world data in order to evaluate and validate a...
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07/19/2022
Expert-LaSTS: Expert-Knowledge Guided Latent Space for Traffic Scenarios
Clustering traffic scenarios and detecting novel scenario types are requ...
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07/18/2022
ExAgt: Expert-guided Augmentation for Representation Learning of Traffic Scenarios
Representation learning in recent years has been addressed with self-sup...
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07/13/2022
Learning Representations for CSI Adaptive Quantization and Feedback
In this work, we propose an efficient method for channel state informati...
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05/24/2022
GMM-based Codebook Construction and Feedback Encoding in FDD Systems
We propose a precoder codebook construction and feedback encoding scheme...
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05/11/2022
Variational Autoencoder Leveraged MMSE Channel Estimation
We propose to utilize a variational autoencoder (VAE) for data-driven ch...
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05/07/2022
Channel Estimation based on Gaussian Mixture Models with Structured Covariances
In this work, we propose variations of a Gaussian mixture model (GMM) ba...
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04/10/2022
Machine Learning-Based CSI Feedback With Variable Length in FDD Massive MIMO
To fully unlock the benefits of multiple-input multiple-output (MIMO) ne...
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11/22/2021
An Asymptotically Optimal Approximation of the Conditional Mean Channel Estimator based on Gaussian Mixture Models
This paper investigates a channel estimator based on Gaussian mixture mo...
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11/18/2021
CSI Clustering with Variational Autoencoding
The model order of a wireless channel plays an important role for a vari...
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10/28/2021
Distributed Joint Multi-cell Optimization of IRS Parameters with Linear Precoders
We present distributed methods for jointly optimizing Intelligent Reflec...
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10/14/2021
Learning a Compressive Sensing Matrix with Structural Constraints via Maximum Mean Discrepancy Optimization
We introduce a learning-based algorithm to obtain a measurement matrix f...
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05/27/2021
Classification and Uncertainty Quantification of Corrupted Data using Semi-Supervised Autoencoders
Parametric and non-parametric classifiers often have to deal with real-w...
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05/19/2021
Unsupervised Learning of Adaptive Codebooks for Deep Feedback Encoding in FDD Systems
In this work, we propose a joint adaptive codebook construction and feed...
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05/05/2021
Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder
Detecting unknown and untested scenarios is crucial for scenario-based t...
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04/11/2021
Learning the CSI Denoising and Feedback Without Supervision
In this work, we develop a joint denoising and feedback strategy for cha...
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04/03/2021
Learning the CSI Recovery in FDD Systems
We propose an innovative machine learning-based technique to address the...
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05/27/2020
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images
A novel unsupervised outlier score, which can be embedded into graph bas...
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12/13/2019
Two-User SIMO Interference Channel with TIN: Improper Signaling versus Time-Sharing
In the two-user Gaussian interference channel with Gaussian inputs and t...
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11/28/2019
Reproducible Evaluation of Neural Network Based Channel Estimators And Predictors Using A Generic Dataset
A low-complexity neural network based approach for channel estimation wa...
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11/17/2019
Learning The MMSE Channel Predictor
We present a neural network based predictor which is derived by starting...
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11/13/2019
Maximizing the Partial Decode-and-Forward Rate in the Gaussian MIMO Relay Channel
It is known that circularly symmetric Gaussian signals are the optimal i...
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10/21/2019
Model Order Selection in DoA Scenarios via Cross-Entropy based Machine Learning Techniques
In this paper, we present a machine learning approach for estimating the...
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10/17/2019
Mixed Monotonic Programming for Fast Global Optimization
While globally optimal solutions to convex programs can be computed effi...
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11/26/2018
hynet: An Optimal Power Flow Framework for Hybrid AC/DC Power Systems
High-voltage direct current (HVDC) systems are increasingly incorporated...
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08/05/2018
Improper Signaling versus Time-Sharing in the Two-User Gaussian Interference Channel with TIN
So-called improper complex signals have been shown to be beneficial in t...
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04/24/2018