Abstract
Nowadays, spectrum in industrial radio systems is already overoccupied. Therefore, future Industry 4.0 applications require coexistence management of different wireless communication systems. For identification of active systems, we propose Compressed Edge Spectrum Sensing (CESS). Here, we focus on practical aspects and show that the sampling rate can still be highly reduced.
Zusammenfassung
Das Spektrum in industriellen Funksystemen ist heutzutage überbelegt. Daher erfordern zukünftige Industrie-4.0-Anwendungen ein Koexistenzmanagement. Zur Identifikation drahtloser Kommunikationssysteme schlagen wir Compressed Edge Spectrum Sensing (CESS) vor. Hier fokussieren wir uns auf praktische Aspekte und zeigen, dass die Abtastrate selbst dann noch stark reduziert werden kann.
Funding source: Allianz Industrie Forschung
Award Identifier / Grant number: 18350 BG/2
Funding statement: This research has been funded by the Federal Ministry for Economic Affairs and Energy of Germany through the AiF in the project KoMe (project number 18350 BG/2).
About the authors
Edgar Beck received his M. Sc. in electrical engineering (with honors) from the University of Bremen in 2017 where he is currently pursuing his Ph. D. degree in electrical engineering at the ANT. Primary field of research: Machine learning, cognitive radio and in particular compressed spectrum sensing.
Carsten Bockelmann received his Ph. D. degree in 2012 in electrical engineering from the University of Bremen, Germany. Currently, he works as a Senior Research Group Leader at the ANT. Primary field of research: Compressive sensing and its application in communication contexts.
Armin Dekorsy is currently the Head of the ANT, University of Bremen, Germany. Before becoming professor, he worked in leading position for industry, e. g., Lucent Technologies and Qualcomm GmbH. Primary field of research: Wireless communication systems, baseband algorithms and digital signal processing.
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