Bachelorarbeiten
Bachelorarbeiten
- Themenbeschreibung: In cooperation with the TU Ilmenau, the Fraunhofer IIS set up a testbed to enable the localization of mobile endpoints using the LPWAN standard mioty for application in current research topics like IoT. The localization is based on time difference of arrival measurements (TDoA).
The mioty standard uses the so-called TSMA (Telegram Splitting Multiple Access) techniques to achieve high robustness against interference. The telegrams consist of single bursts that are pseudo-randomly distributed in frequency and time. However, the long transmission duration of a single telegram (up to 4s) in combination with noisy oscillators can cause severe degradation of the localization accuracy. One way to become more robust against this effect is to adjust the distribution of the individual bursts in time and frequency. In the context of this work, various possibilities are to be investigated as to how this waveform could be modified.
The results achieved in the thesis are to be presented extensively in a written elaboration. The program source code must be sufficiently commented. The DFG rules for good scientific practice are to be respected in the preparation of the thesis. The execution of the work can be done in English as well as in German language.
In detail, the tasks mentioned above are to be conducted:
- Literature research on the principle of TDoA localization and Phase noise and on the mioty standard according to ETSI TS 103 357
- Familiarization with the existing simulation framework
- Optimization and modification of the existing waveform
- Conducting simulations with the adapted waveforms and compare the results to the standard waveform
- Verification of the results in real-world measurements
- Themenbeschreibung: Localization is a critical component in many modern applications, ranging from tracking equipment in industrial facilities to monitoring livestock in agricultural settings, such as dairy fields. One effective approach for localization is Time-Difference-of-Arrival (TDoA), which relies on precise synchronization between receivers to achieve accurate results.
At LIKE we are working on a state-of-the-art synchronization system based on Signals of Opportunity (SoO). These are signals that were originally intended for a different use, e.g. DAB or DVB-T. When processing these signals, relevant parameters can be extracted that are needed for precise synchronization. Currently this synchronization system is deployed in a CloudRAN, where large amounts of SoO data need to be transmitted between base stations.
In order to reduce the amount of data that is transmitted, different forms of compression can be applied. The goal of this work is to look into more detail on different compression techniques and lossy compressors for the specific case of synchronization with SoO. Some methods were already investigated in recent works and future work can build upon these results.
The obtained outcomes are to be recorded within a written report. Furthermore, the developed source code must be annotated with comments to ensure clarity and understanding. Additionally, the student is required to follow the guidelines established by the DFG (German Research Foundation) regarding Good Scientific Practice.
During this research project, the following tasks will be undertaken:
- Literature research on receiver synchronization
- Familiarization with synchronization and compression framework
- Extensive literature research on compression techniques (algorithms, quantization)
- Implementation of different compressors
- Evaluation of implemented compressors regarding the effects on synchronization performance on simulated and real-world data
- Themenbeschreibung: The thesis aims to implement and evaluate machine learning algorithms for calculating
blood pressure on embedded devices. The embedded algorithms shall be optimized for
low power consumption, a minimal resource overhead and scored against existing
benchmarks.
This thesis will explore low-power algorithms for continuous blood pressure monitoring on embedded devices. The findings could help deploy algorithms for blood pressure calculation with ECG and PPG signals for cuffless measurements to embedded devices.
- Themengebiete:
- Voraussetzungen:
- Betreuer: Jürgen Frickel & Markus Jechow
- Hochschullehrer: Prof. Dr.-Ing. Albert Heuberger
- PDF: Aushang
Anfragen zu Themen und der Betreuung einer BA-Arbeit können sie auch unabhängig von den ausgeschriebenen Themen direkt an die Ansprechpartner der jeweiligen Forschungsschwerpunkte schicken.
Telemetrie
Satellitenkommunikation
Navigation und Ortsbestimmung / GPS und Allg.
