This image shows Marvin Geiselhart, M.Sc.

Marvin Geiselhart, M.Sc.

Research Assistant
Institute of Telecommunications

Contact

Pfaffenwaldring 47 (ETI 2)
70569 Stuttgart
Germany
Room: 2.332

Subject

Research

Error-correcting codes (channel codes) are the workhorse of modern communication systems, enabling reliable transmissions close to the theoretical limits. Emerging applications like industry automation, autonomous driving, remote surgery and many more require ultra reliable communication with low latency.

My research focusses on channel codes and decoding algorithms allowing low latency and high reliabality. For this reason, I examine codes with rich symmetries, whose decoding can be highly parallelized. Some key concepts I consider are:

  • Polar codes and polar-like codes
  • Low-density parity check (LDPC) codes
  • Low latency, low complexity decoding algorithms, such as automorphism ensemble decoding (AED) and iterative decoding
  • Optimization and Machine Learning

For more details, please have a look at my publications below.

Student Projects / Theses

I offer usually many bachelor, research or master thesis topics along the lines of

  • Topics from my current research, such as code design, decoder design, decoder implementation, system design ...
  • Webdemo conception and implementation
  • Demonstrators

If you are a student interested in these or similar topics, feel free to contact me.

Teaching

I also enjoy building webdemos and interactive programs to make communications more approachable and exploring its concepts playful.

The following interactive program demonstrates the concept of geometric shaping. For different arrangements ("constellations") of the transmit symbols in the I/Q-plane, one can communicate different amount of information per symbol through an AWGN channel. Drag the constellation points with your mouse and see how close you can get to Shannon's capacity curve (hint: not only the positions, but also the labeling, i.e. the corresponding bit patterns, matter)!

The mutual information curve is computed via Monte Carlo simulation of thousands of bits in your browser in real time. Implemented in p5js.

 
  1. 2023

    1. M. Geiselhart, J. Clausius, and S. ten Brink, “Rate-Compatible Polar Codes for Automorphism Ensemble Decoding,” in 2023 12th International Symposium on Topics in Coding (ISTC), 2023, pp. 1–5.
    2. L. Johannsen, C. Kestel, M. Geiselhart, T. Vogt, S. ten Brink, and N. Wehn, “Successive Cancellation Automorphism List Decoding of Polar Codes,” in 2023 12th International Symposium on Topics in Coding (ISTC), 2023, pp. 1–5.
    3. J. Clausius, M. Geiselhart, and S. Ten Brink, “Component Training of Turbo Autoencoders,” in 2023 12th International Symposium on Topics in Coding (ISTC), 2023, pp. 1–5.
    4. M. Geiselhart, M. Gauger, F. Krieg, J. Clausius, and S. ten Brink, “Phase-Equivariant Polar Coded Modulation,” in 2023 12th International Symposium on Topics in Coding (ISTC), 2023, pp. 1–5.
    5. A. Zunker, M. Geiselhart, and S. ten Brink, “Enumeration of Minimum Weight Codewords of Pre-Transformed Polar Codes by Tree Intersection.” 2023 [Online]. Available: https://arxiv.org/abs/2311.17774
    6. C. Kestel, M. Geiselhart, L. Johannsen, S. ten Brink, and N. Wehn, “Automorphism Ensemble Polar Code Decoders for 6G URLLC,” 2023.
    7. M. Geiselhart, M. Gauger, F. Krieg, J. Clausius, and S. ten Brink, “Phase-Equivariant Polar Coded Modulation,” 2023 [Online]. Available: https://arxiv.org/abs/2305.01972
    8. A. Zunker et al., “Row-Merged Polar Codes: Analysis, Design and Decoder Implementation.” 2023 [Online]. Available: https://arxiv.org/abs/2312.14749
    9. M. Geiselhart, F. Krieg, J. Clausius, D. Tandler, and S. ten Brink, “6G: A Welcome Chance to Unify Channel Coding?,” IEEE BITS the Information Theory Magazine, pp. 1–12, 2023.
    10. M. Geiselhart, J. Clausius, and S. ten Brink, “Rate-Compatible Polar Codes for Automorphism Ensemble Decoding,” 2023 [Online]. Available: https://arxiv.org/abs/2305.01214
  2. 2022

    1. M. Geiselhart et al., “Learning Quantization in LDPC Decoders,” in 2022 IEEE Globecom Workshops (GC Wkshps), 2022, pp. 467–472.
    2. M. Geiselhart, A. Elkelesh, J. Clausius, and S. ten Brink, “A Polar Subcode Approach to Belief Propagation List Decoding,” in 2022 IEEE Information Theory Workshop (ITW), 2022, pp. 243–248.
    3. M. Geiselhart, A. Zunker, A. Elkelesh, J. Clausius, and S. ten Brink, “Graph Search based Polar Code Design.” Nov-2022 [Online]. Available: http://arxiv.org/abs/2211.16010
    4. M. Geiselhart, A. Zunker, A. Elkelesh, J. Clausius, and S. ten Brink, “Graph Search based Polar Code Design,” in 2022 56th Asilomar Conference on Signals, Systems, and Computers, 2022, pp. 387–391.
    5. M. Geiselhart, A. Elkelesh, J. Clausius, and S. ten Brink, “A Polar Subcode Approach to Belief Propagation List Decoding,” 2022 [Online]. Available: http://arxiv.org/abs/2205.06631
    6. J. Clausius, M. Geiselhart, and S. ten Brink, “Optimizing Serially Concatenated Neural Codes with Classical Decoders.” 2022.
    7. M. Geiselhart et al., “Learning Quantization in LDPC Decoders.” 2022 [Online]. Available: http://arxiv.org/abs/2208.05186
    8. M. Geiselhart, M. Ebada, A. Elkelesh, J. Clausius, and S. ten Brink, “Automorphism Ensemble Decoding of Quasi-Cyclic LDPC Codes by Breaking Graph Symmetries.” 2022 [Online]. Available: http://arxiv.org/abs/2202.00287
    9. M. Geiselhart, M. Ebada, A. Elkelesh, J. Clausius, and S. ten Brink, “Automorphism Ensemble Decoding of Quasi-Cyclic LDPC Codes by Breaking Graph Symmetries,” IEEE Communications Letters, pp. 1–1, 2022.
  3. 2021

    1. M. Geiselhart, A. Elkelesh, M. Ebada, S. Cammerer, and S. ten Brink, “On the Automorphism Group of Polar Codes,” in 2021 IEEE International Symposium on Information Theory (ISIT), 2021, pp. 1230–1235.
    2. M. Geiselhart, A. Elkelesh, M. Ebada, S. Cammerer, and S. Ten Brink, “Automorphism Ensemble Decoding of Reed—Muller Codes,” IEEE Transactions on Communications, pp. 1–1, 2021.
    3. M. Geiselhart, A. Elkelesh, M. Ebada, S. Cammerer, and S. ten Brink, “Iterative Reed-Muller Decoding,” 2021 [Online]. Available: http://arxiv.org/abs/2107.12613
    4. M. Geiselhart, A. Elkelesh, M. Ebada, S. Cammerer, and S. ten Brink, “On the Automorphism Group of Polar Codes,” 2021 [Online]. Available: http://arxiv.org/abs/2101.09679
  4. 2020

    1. M. Ebada, S. Cammerer, A. Elkelesh, M. Geiselhart, and S. ten Brink, “Iterative Detection and Decoding of Finite-Length Polar Codes in Gaussian Multiple Access Channels,” in 2020 54th Asilomar Conference on Signals, Systems, and Computers, 2020, pp. 683–688 [Online]. Available: https://ieeexplore.ieee.org/document/9443374
    2. M. Geiselhart, A. Elkelesh, M. Ebada, S. Cammerer, and S. ten Brink, “CRC-Aided Belief Propagation List Decoding of Polar Codes,” in 2020 IEEE International Symposium on Information Theory (ISIT), 2020, pp. 395–400 [Online]. Available: https://ieeexplore.ieee.org/document/9174249
    3. M. Geiselhart, A. Elkelesh, M. Ebada, S. Cammerer, and S. ten Brink, “Automorphism Ensemble Decoding of Reed-Muller Codes,” 2020 [Online]. Available: http://arxiv.org/abs/2012.07635
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