Forschungspraktika

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

Themengebiete: Signal Processing, Synchronization, Python

Voraussetzungen: Good Knowledge in Python, Basic Signal Processing Knowledge

Betreuer: Sebastian Klob

Hochschullehrer: Prof. Dr.-Ing. JÃ¶rg Robert

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