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Internships (Praxissemester)
Internships are part of the curricula in Information Technology and Informatics. An internship consists of a 12-week supervised project in a company or research lab. The tasks of the intern are similar to those of a graduated engineer. Following the internship the experiences gained are to be explained in a report, scientifically deliberated and presented in form of a lecture. Together with a confirmation from the company, the report is to be submitted to the supervising professor.
Mobile Systems
| Synchronization over Optical Networks for Multi-Cell MIMO |
| Status | available |
| Contact | Docomo Euro Labs Munich, Germany |
| E-Mail | |
| Description | Synchronization is a very important issue in cellular networks. Base stations need a common reference for frequency and time, so that they transmit in the correct frequency band and possibly cooperate to transmit simultaneously to improve the throughput of cell edge users.
The goals of the internship are related to this scenario and are as follows:
- Investigate the impact of synchronization over digital optical networks for multi‐cell MIMO schemes
- Define pros and cons of the optical network architecture for synchronization
- Examine the impact of clock quality on the synchronization accuracy
- Develop a simulation tool that models realistic synchronization errors
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| PDF-Download |
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| Exploring Self-Organizing Systems |
| Status | available |
| Advisor | Wilfried Elmenreich |
| Contact | Wilfried Elmenreich |
| E-Mail | |
| Phone | +43 (0)463 2700 3649 |
| Description | Within the DEMESOS project we research the evolutionary design of self-orgainizing systems. Therefore, we developed a framework that allows to evolve a neural network controller for a multi-agent system such that the actions of the agents drive the system towards an intended state. An example could be to evolve the neural controllers for a team of robots in order to achieve a collaborative task.
This internship can be done one of the following two ways:
(i) implement a new problem domain within the framework and evaluate how well the neural controllers can be evolved to solve the task.
(ii) implement a new representation for the controller (e.g. Spiking Neural Networks) and apply it to existing problem domain implementations.
Requirements: good Java programming skills, interest in neural networks and genetic algorithms |
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