activity
20112025
most citedLikelihood Consensus and Its Application to Distributed Particle Filtering

225 citations · 735 across the 19 of their papers we have counts for

collaborators

21 papers

eess.SP2025★ 3 cited

Identification of RIS-Assisted Paths for Wireless Integrated Sensing and Communication

Zeyu Huang, Stefan Schwarz, Bashar Tahir +1

Distinguishing between reconfigurable intelligent surface (RIS) assisted paths and non-line-of-sight (NLOS) paths is a fundamental problem for RIS-assisted integrated sensing and c…

eess.SP2023★ 22 cited

Self-Supervised and Invariant Representations for Wireless Localization

Artan Salihu, Stefan Schwarz, Markus Rupp

In this work, we present a wireless localization method that operates on self-supervised and unlabeled channel estimates. Our self-supervising method learns general-purpose channel…

eess.SP2022★ 16 cited

Attention Aided CSI Wireless Localization

Artan Salihu, Stefan Schwarz, Markus Rupp

Deep neural networks (DNNs) have become a popular approach for wireless localization based on channel state information (CSI). A common practice is to use the raw CSI in the input…

cs.IT2022★ 1 cited

Impact of Channel Correlation on Subspace-Based Activity Detection in Grant-Free NOMA

Bashar Tahir, Stefan Schwarz, Markus Rupp

In this paper, we consider the problem of activity detection in grant-free code-domain non-orthogonal multiple access (NOMA). We focus on performing activity detection via subspace…

eess.SP2021

Learning-based Remote Radio Head Selection and Localization in Distributed Antenna System

Artan Salihu, Stefan Schwarz, Markus Rupp

In this work, we consider estimating user positions in a spatially distributed antenna system (DAS) from the uplink channel state information (CSI). However, with the increased num…

eess.SP2021

Towards Scalable Uncertainty Aware DNN-based Wireless Localisation

Artan Salihu, Stefan Schwarz, Markus Rupp

Existing deep neural network (DNN) based wireless localization approaches typically do not capture uncertainty inherent in their estimates. In this work, we propose and evaluate va…