Armin Schuster - Institute for Electronics Engineering

Armin Schuster, M. Sc.

Department of Electrical-Electronic-Communication Engineering
Chair of Electronics (Prof. Dr. Weigel)

Room 04.232
Cauerstraße 9
91058 Erlangen

Curriculum Vitæ

since 2021	Researcher, Institute for Electronics Engineering, Friedrich-Alexander-University Erlangen-Nürnberg
2020-2021	Researcher, Department of Computer Science 12 (Hardware/Software Co-Design), Friedrich-Alexander-University Erlangen-Nürnberg
2017-2020	M.Sc. Information and Communication Technology, Friedrich-Alexander University Erlangen-Nürnberg
2018-2019	Exchange Year, NTNU Trondheim, Norway
2013-2017	B.Eng. Electrical Engineering and Information Technology, TH Nürnberg
1994	Born in Roth, Germany

Area of Research

Mobile Communications, 6G

Awards

Master Prize Siemens Corporate Technology

Publications

Schuster A., Reißland T., Weigel R.:
Hybrid Sensing and Communications Receiver Front-End for Mobile Communications Applications
2023 IEEE MTT-S Latin America Microwave Conference (LAMC) (San Jose, 06/12/2023 - 08/12/2023)
DOI: 10.1109/LAMC59011.2023.10375541
URL: https://ieeexplore.ieee.org/abstract/document/10375541
BibTeX: Download

Schuster A., Erhardt S., Reißland T., Weigel R.:
Design and Analysis of a RF Front-End Receiver System Based on Multi-Layer Organic Filtering for Sub-6 GHz Mobile Communication Applications
2023 IEEE Radio and Wireless Symposium (Las Vegas, Nevada, USA, 22/01/2023 - 25/01/2023)
In: IEEE Radio and Wireless Symposium, RWS 2023
DOI: 10.1109/RWS55624.2023.10046331
URL: https://ieeexplore.ieee.org/document/10046331
BibTeX: Download

Schuster A., Heidorn C., Brand M., Keszöcze O., Teich J.:
Design Space Exploration of Time, Energy, and Error Rate Trade-oﬀs for CNNs using Accuracy-Programmable Instruction Set Processors
2nd International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning (ITEM) (Virtual Event, 13/09/2021 - 17/09/2021)
In: Springer, Cham (ed.): Joint European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Switzerland: 2021
DOI: 10.1007/978-3-030-93736-2_29
BibTeX: Download