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)
Thesis in Polar Coding, Probabilistic Shaping, and Applied Information Theory
Description
I may not always have prepared thesis topics available. Please feel free to reach out if you are interested in working on a thesis within any of my research areas.
Channel resolvability, introduced in [1] based on ideas from [2], measures how much needs to be transmitted to approximate a random variable at the channel output accurately.
Not only does it have deep ties to the capacity of a channel, but it is also an important tool in information theoretic secrecy, e.g., when communication should be hidden.
The goal of this topic is to understand and present the concept of resolvability, to outline it's relation to other channel properties such as capacity, and to illustrate its use in information theory by means of an exemplary application.
Han, Verdu. 1993. Approximation Theory of Output Statistics. https://doi.org/10.1109/18.256486
Wyner. 1975. The common information of two dependent random variables. https://doi.org/10.1109/TIT.1975.1055346
Prerequisites
Information Theory
Multi-User Information Theory is helpful but not necessary
Vector Quantization with Convolutional Codes, 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
Publications
2024
Runge, C.: Time-Shifted Alternating Gelfand Pinsker Coding. European School of Information Theory (ESIT), 2024Eindhoven, Netherlandsmore…
Runge, C.: Improved list-decoding for polar coded shaping. Munich Workshop on Shannon Coding Techniques (MSCT), 2024Munich, Germanymore…
Runge, C.: Improved list-decoding for polar coded shaping. Munich Workshop on Coding and Cryptography (MWCC), 2024Munich, Germanymore…
Runge, C.; Kramer, G.: Time-Shifted Alternating Gelfand-Pinsker Coding for Broadcast Channels. IEEE International Symposium on Information Theory (ISIT), IEEE, 2024Athens, Greece, 1700-1705 more…
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2023
Runge, C.: Polar Shaped Hamming Codes. Joint Workshop on Communications and Coding (JWCC), 2023Garmisch-Partenkirchen, Germanymore…
Runge, C.: List Decoding for Polar-Coded Probabilistic Shaping. European School of Information Theory (ESIT), 2023Bristol, UKmore…
Runge, C.; Wiegart, T.; Lentner, D.: Improved List Decoding for Polar-Coded Probabilistic Shaping. 12th International Symposium on Topics in Coding (ISTC), IEEE, 2023Brest, Francemore…
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2022
Runge, C.: Channel Polarization, Probabilistic Shaping, and Binning. Munich Doctoral Seminar on Communications, 2022 more…
Runge, C.: Polar Distribution Matching with Hard Constraints. European School of Information Theory (ESIT), 2022Vienna, Austriamore…
Runge, C.; Wiegart, T.; Lentner, D.; Prinz, T.: Multilevel Binary Polar-Coded Modulation Achieving the Capacity of Asymmetric Channels. IEEE International Symposium on Information Theory (ISIT), 2022Espoo, Finlandmore…
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2021
Runge, C.: Higher-Order Polar-Coded Modulation for Asymmetric Channels. Master's Thesis (won Ralf Kötter memorial award), 2021 more…
Full text (mediaTUM)
Runge, C.: Higher-Order Polar Coded Modulation with Arbitrary Probabilistic Shaping. Ferienakademie 2021: Advanced Topics in Information Theory and Communications, 2021Sarentino, Italymore…
