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http://dx.doi.org/10.25673/111741| Title: | 5G-based localization in industrial environments |
| Author(s): | Frischkorn, Bjarne Knitter, Michael Endemann, Wolfgang Kays, Rüdiger |
| Issue Date: | 2023 |
| Type: | Conference object |
| Language: | English |
| URN: | urn:nbn:de:gbv:ma9:1-1981185920-1136989 |
| Subjects: | 5G Survey Indoor Rising Edge Localization |
| Abstract: | This paper focuses on challenges occurring when using the 5G NR standard as a real- world application for precise localization in industrial environments. The different aspects of a mobile network based localization approach are discussed. First an overview on mobile network setup is given. Based on a mobile network emulation a first localization is conducted in an indoor laboratory. Afterwards the influence of indoor channel properties and the arising problems are discussed. With the results from this discussion, a new system model is introduced to improve the localization accuracy down to one meter. |
| URI: | https://opendata.uni-halle.de//handle/1981185920/113698 http://dx.doi.org/10.25673/111741 |
| Open Access: |  Open access publication |
| License: |  (CC BY-SA 4.0) Creative Commons Attribution ShareAlike 4.0 |
| Related Resource (URI): | https://opendata.uni-halle.de//handle/1981185920/113590 |
| Appears in Collections: | Fakultät für Elektrotechnik und Informationstechnik (OA) |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 15_KommA2023_P-7_Frischkorn et al..pdf | Paper | 607.77 kB | Adobe PDF |  View/Open |