Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Thomae, Reiner S."'
Autor:
Andrich, Carsten, Nowack, Tobias F., Ihlow, Alexander, Giehl, Sebastian, Engelhardt, Maximilian, Sommerkorn, Gerd, Schwind, Andreas, Hofmann, Willi, Bornkessel, Christian, Thomä, Reiner S., Hein, Matthias A.
The upcoming 6G mobile communication standard will offer a revolutionary new feature: Integrated sensing and communication (ISAC) reuses mobile communication signals to realize multi-static radar for various applications including localization. Conse
Externí odkaz:
http://arxiv.org/abs/2407.13749
Utilizing deep learning (DL) techniques for radio-based positioning of user equipment (UE) through channel state information (CSI) fingerprints has demonstrated significant potential. DL models can extract complex characteristics from the CSI fingerp
Externí odkaz:
http://arxiv.org/abs/2405.11816
Deep learning (DL) methods have been shown to improve the performance of several use cases for the fifth-generation (5G) New radio (NR) air interface. In this paper we investigate user equipment (UE) positioning using the channel state information (C
Externí odkaz:
http://arxiv.org/abs/2403.08565
Autor:
Beuster, Julia, Smeenk, Carsten Jan, Myint, Saw James, Faramarzahanagri, Reza, Andrich, Carsten, Giehl, Sebastian, Schneider, Christian, Thomä, Reiner S.
With the upcoming multitude of commercial and public applications envisioned in the mobile 6G radio landscape using unmanned aerial vehicles (UAVs), integrated sensing and communication (ISAC) plays a key role to enable the detection and localization
Externí odkaz:
http://arxiv.org/abs/2402.16591
Autor:
Costa, Heraldo Cesar Alves, Myint, Saw James, Andrich, Carsten, Giehl, Sebastian W., Schneider, Christian, Thomä, Reiner S.
Publikováno v:
2024 IEEE Radar Conference (RadarConf24)
Integrated Sensing and Communication (ISAC) comprises detection and analysis of non-cooperative targets by exploiting the resources of the mobile radio system. In this context, micro-Doppler is of great importance for target classification, in order
Externí odkaz:
http://arxiv.org/abs/2401.14287
Autor:
Costa, Heraldo Cesar Alves, Myint, Saw James, Andrich, Carsten, Giehl, Sebastian W., Schneider, Christian, Thomä, Reiner S.
The integration of wireless communication and radar sensing is gaining the interest of researchers from wireless communication and radar societies. Sensing in Integrated Communication and Sensing (ICAS) systems differs from the traditional radar syst
Externí odkaz:
http://arxiv.org/abs/2401.14448
Autor:
Foliadis, Anastasios, Garcia, Mario H. Castañeda, Stirling-Gallacher, Richard A., Thomä, Reiner S.
Radio based positioning of a user equipment (UE) based on deep learning (DL) methods using channel state information (CSI) fingerprints have shown promising results. DL models are able to capture complex properties embedded in the CSI about a particu
Externí odkaz:
http://arxiv.org/abs/2210.14510
Autor:
Thomä, Reiner S., Andrich, Carsten, Beuster, Julia, Costa, Heraldo Cesar Alves, Giehl, Sebastian, Myint, Saw James, Schneider, Christian, Sommerkorn, Gerd
Integrated sensing and communication (ISAC) qualifies mobile radio systems for detecting and localizing of passive objects by means of radar sensing. Advanced ISAC networks rely on meshed mobile radio access nodes (infrastructure and/or user equipmen
Externí odkaz:
http://arxiv.org/abs/2210.11840
Autor:
Foliadis, Anastasios, Garcia, Mario H. Castañeda, Stirling-Gallacher, Richard A., Thomä, Reiner S.
Deep learning (DL) methods have been recently proposed for user equipment (UE) localization in wireless communication networks, based on the channel state information (CSI) between a UE and each base station (BS) in the uplink. With the CSI from the
Externí odkaz:
http://arxiv.org/abs/2111.11839
Autor:
Foliadis, Anastasios, Garcia, Mario H. Castañeda, Stirling-Gallacher, Richard A., Thomä, Reiner S.
In this paper we study the use of the Channel State Information (CSI) as fingerprint inputs of a Convolutional Neural Network (CNN) for localization. We examine whether the CSI can be used as a distinct fingerprint corresponding to a single position
Externí odkaz:
http://arxiv.org/abs/2101.08983