Biography

• Doctoral researcher at the Chair of Communications Engineering at TUM since October 2021
• M.Sc. in Electrical Engineering and Information Technology at TUM, 2019 - 2021
• B.Sc. in Electrical Engineering and Information Technology at TUM, 2015 - 2019

Research Interests

Distribution Matching and Probabilistic Shaping

It is often desirable to send different channel input symbols with different relative frequencies. The motivation comes from Shannon's capacity formula, which tells us that the maximal transmission rate is generally achieved for some specific channel input distribution. With linear encoders, one can only obtain symbols that are equally likely. By employing techniques similar to lossless or lossy source coding, one can design coding schemes that adapt the marginal distribution of the symbols in the modulated code words.

Coding for Multi-user Scenarios

In communications scenarios with multiple transmitters or receivers, achievability proofs are typically based on random coding and some form of exponential-complexity decoding. It is thus of interest to design practically feasible coding schemes for these scenarios that can recover the rate or SNR gains promised by theory.

Coded Modulation

In order to achieve higher spectral efficiencies, it is necessary to encode multiple bits per channel use or, in other words, to use higher-order constellations. In order to operate close to the Shannon capacity, it is typically necessary to employ channel coding.

Theory of Modern Channel Coding

In particular polar coding. Polar codes are a class of codes that are shown to be asymptotically optimal in various channel and source coding problems, i.e., they achieve capacity or entropy. Additionally, combined with simple outer codes, they yield very competitive codes at short to medium block lengths. Their decoding and analysis are based mainly on probability theory, while certain analyses from algebraic coding theory are also applicable.

Information Theory and its Applications

I'm always interested in various aspects of information theory and communications engineering.

Teaching

• Advanced Topics in Communications Engineering: Lossless Source Coding (SS22)
• Multi-user Information Theory (SS23)
• Seminar on Digital Communications (WS23/24)
• Digital Communications for TUM Asia (SS24, SS25)
• Wireless Communications Laboratory (SS24, SS25)
• Wireless Communications (WS25/26)

Supervised Theses

• Distribution Matching with Quantised Trellises, Engineering Internship
• Hard-Decision Decoding of Polar Codes, Engineering Internship
• Hard-Decision List Decoding of Polar Codes, Bachelor's Thesis
• Quantized Enumerative Sphere Shaping, Bachelor's Thesis (won Walter Gademann thesis award)
• Vector Quantization with Convolutional Codes, Bachelor's Thesis
• Polar Code Construction for Dirty-Paper Coding, Bachelor's Thesis
• Investigation of Improved Decoding for Polar Coded Shaping, Research Internship
• Bit-Flipping Encoding for Polar Shaping, Research Internship
• Polar Coded Shaping Scheme for IR-HARQ, Master's Thesis
• Probabilistic Shaping with Low-Density Graph Codes and Message Passing, Master's Thesis
• Entropy Estimation and Compression Scheme for Wildfire Detection, Master's Thesis
• Polar Codes for Stealth Communication, Master's Thesis
• Construction of Shaped Polar Codes for List Decoding using Reinforcement Learning, Master's Thesis