249 citations · 374 across the 50 of their papers we have counts for
13 papers · 1 filter
Bayesian Self-Calibration and Parametric Channel Estimation for 6G Antenna Arrays
Patrick Hödl, Jakob Möderl, Erik Leitinger +1
Accurate channel estimation is essential for both high-rate communication and high-precision sensing in 6G wireless systems. However, a major performance limitation arises from cal…
General Pruning Criteria for Fast SBL
Jakob Möderl, Erik Leitinger, Bernard Henri Fleury
Sparse Bayesian learning (SBL) associates to each weight in the underlying linear model a hyperparameter by assuming that each weight is Gaussian distributed with zero mean and pre…
Optimizing Sparse Antenna Arrays for Localization and Sensing using Vector Spherical Wave Functions
Tobias Lafer, Erik Leitinger, Klaus Witrisal
In increasing number of electronic devices implement wideband radio technologies for localization and sensing purposes, like ultra-wideband (UWB). Such radio technologies benefit f…
Robust Localization in Modern Cellular Networks using Global Map Features
Junshi Chen, Xuhong Li, Russ Whiton +2
Radio frequency (RF) signal-based localization using modern cellular networks has emerged as a promising solution to accurately locate objects in challenging environments. One of t…
Multi-Sensor Fusion for Extended Object Tracking Exploiting Active and Passive Radio Signals
Hong Zhu, Alexander Venus, Erik Leitinger +1
Reliable and robust positioning of radio devices remains a challenging task due to multipath propagation, hardware impairments, and interference from other radio transmitters. A fr…
Low-latency D-MIMO Localization using Distributed Scalable Message-Passing Algorithm
Dumitra Iancu, Liang Liu, Ove Edfors +2
Distributed MIMO and integrated sensing and communication are expected to be key technologies in future wireless systems, enabling reliable, low-latency communication and accurate…
Adaptive Multipath-Based SLAM for Distributed MIMO Systems
Xuhong Li, Benjamin J. B. Deutschmann, Erik Leitinger +1
Localizing users and mapping the environment using radio signals is a key task in emerging applications such as low-latency communications and safety-critical navigation. Recently…
Posterior Cramér-Rao Bounds on Localization and Mapping Errors in Distributed MIMO SLAM
Benjamin J. B. Deutschmann, Xuhong Li, Florian Meyer +1
Radio-frequency simultaneous localization and mapping (RF-SLAM) methods jointly infer the position of mobile transmitters and receivers in wireless networks, together with a geomet…
Multi-Sensor Fusion of Active and Passive Measurements for Extended Object Tracking
Hong Zhu, Alexander Venus, Erik Leitinger +1
This paper addresses the challenge of achieving robust and reliable positioning of a radio device carried by an agent, in scenarios where direct line-of-sight (LOS) radio links are…
Geometry-Based Channel Estimation, Prediction, and Fusion
Benjamin J. B. Deutschmann, Erik Leitinger, Klaus Witrisal
Reciprocity-based beamforming-most commonly employed in time-division duplexing-uses noisy, estimated (i.e., measured) channel state information (CSI) acquired on the uplink. While…
Variational Message Passing-based Multiobject Tracking for MIMO-Radars using Raw Sensor Signals
Anders Malthe Westerkam, Jakob Möderl, Erik Leitinger +1
In this paper, we propose a direct multiobject tracking (MOT) approach for MIMO-radar signals that operates on raw sensor data via variational message passing (VMP). Unlike classic…
A Sigma Point-based Low Complexity Algorithm for Multipath-based SLAM in MIMO Systems
Anna Masiero, Alexander Venus, Erik Leitinger
Multipath-based simultaneous localization and mapping (MP-SLAM) is a promising approach in wireless networks to jointly obtain position information of transmitters/receivers and in…
A Block-Sparse Bayesian Learning Algorithm with Dictionary Parameter Estimation for Multi-Sensor Data Fusion
Jakob Möderl, Anders Malte Westerkam, Alexander Venus +1
We propose an sparse Bayesian learning (SBL)-based method that leverages group sparsity and multiple parameterized dictionaries to detect the relevant dictionary entries and estima…