The Institute for Communications Technology, Department of Mobile Radio Systems (Prof. Kürner) offers a job as a scientific assistant (TV-L E13) with a limited contract until 31.12.2022 (prolongation possible).
The tasks include research work in Car-to-X communication in the frame of a project funded by the Bundesministerium für Verkehr und digitale Infrastruktur.
The candidate is required to have a completed Master’s degree in Electrical Engineering or Information Technology – preferably with a focus on Communications Technology or High Frequency Technology – with a finale grade of “good” or better.
Previous knowledge in mobile communications, especially in the areas of modeling, simulating and measuring mobile radio systems, e.g. through participation in the corresponding lectures or by a respective focus of the Master’s thesis, would be helpful. Fluent English in oral and written form is of advantage. It is intended that project exceeds the aforementioned time frame. A doctorate opportunity will be possible.
In addition to the research tasks and to a smaller extent, the position will also include tasks in teaching such as supervising Bachelor’s and Master’s theses and supervising lectures at the institute.
The salary depends on the assigned tasks and fulfillment of personal requirements and ranges up to salary group E 13 TV-L. The position is generally suitable for part-time employment but should be staffed 100 percent.
Candidates with disabilities will be preferred if equally qualified (in that case, please attach proof of disability). Applications from international candidates are welcome. TU Braunschweig seeks to reduce underrepresentation in the sense of the NGG in all areas and positions. Therefore, applications from women are highly welcome.
Please note that personal data and will be stored for the purpose of the application process.
Please note that application costs cannot be refunded. Applications can only be returned when a self-addressed, sufficiently stamped envelope is provided.
Deriving capacities of memoryless multi-user (MU) channels usually relies on information-theoretic (IT) orders such as degraded, less noisy, or more capable, etc. When there is no instantaneous channel state information at the transmitter (CSIT), identifying whether an MU channel satisfies a certain IT order or not is usually not trivial. This makes deriving capacity results in this case much more involved than in cases with perfect CSIT. For example, when solely statistical CSIT is available, capacity is known only for very few cases such as the layered broadcast (BC), the binary fading interference channel (IC) under weak and strong interference, the one-sided layered IC, and the Gaussian wiretap channel (GWTC) under certain conditions. Our group has partly answered the following questions for fast fading Gaussian BC, Gaussian IC with strong and very strong interferences, and Gaussian WTC under statistical CSIT: When is it possible to reorder the realizations of random channel gains between different transmitter-receiver pairs to obtain an equivalent channel, such that the new channel gains satisfy a certain IT order within one codeword length? Besides, how to construct such equivalent channels? Finally, what are the capacity results?
Tasks: In this work, we aim to broaden our investigation of the aforementioned open problems. More specifically, recently, we have explicitly adopted the rate splitting from the Han-Kobayashi (HK) coding scheme with a non-uniform time sharing (TS), to analyze the achievable rate of an fast fading asymmetric B-IC with moderate interference with statistical CSIT, whose capacity region is still open. In this work, you will work closely with me on generalizing the scheme of HK coding with TS in the following 2 possible directions: 1. By inserting more degree of freedom on the HK code with respect to TS. 2. Considering a higher dimension of TS. We will publish our results in international conferences and/or journal.
Requirements: • High interests on mathematical modeling and theoretical analysis • Sufficient background knowledge of information theory