Caspar v. Lengerke

M.Sc. Caspar v. Lengerke

PhD Researcher

Caspar v. Lengerke studied Electrical Engineering at RWTH Aachen University and received his Bachelor’s and Master’s degree in 2017 and 2019 respectively. For his Master’s thesis he worked on Machine Learning in the Physical Layer and stayed for his compulsory internship with Nokia Bell Labs in Stuttgart. Thereafter, he studied Economics at Heidelberg University before joining the Deutsche Telekom Chair of Communication Networks at TU Dresden in July 2021.

His research focuses on goal-oriented communication. Since current communication methods are getting closer and closer to the theoretical limit postulated by Claude Shannon 70 years ago, new avenues of research are necessary to find ways to still the demand for even more connectivity in the future. While Shannon considered the goal of any communication to be irrelevant to the underlying engineering task, information theorists have found the opposite to be true. Any communication goal can be achieved using Shannon’s understanding of communication, but certain goals can be achieved by transmitting significantly less data than Shannon’s theory demands. Goal-oriented communication allows for drastic improvements over traditional communication methods by exploiting knowledge of the goal of the communication, and utilisation of previously useless resources like common randomness and noiseless feedback to increase the channel capacity.

Prominent examples of communication goals with significant proven gains over Shannon’s view include identification via channels and common randomness generation. In identification, the goal of the communication is for the receiver to verify in a binary hypothesis test whether the transmitter sent a specific identity or not. This is, for example, of interest in massive machine-type communications and digital twin applications. Common randomness generation allows for two parties to agree on a certain amount of random data by transmitting less data than finally agreed upon. Common randomness is of special interest for security applications and significantly increases identification capacity.


Phone: +49 351 463-40863
Office: BAR I41a

Research Interests:

  • Goal-oriented Communications
  • Practical Identification Codes
  • Common Randomness Generation


Post-Shannon Theory and Implementation


Summer 22

  • Fundamentals of Electrical Engineering 2

Winter 21/22


Diploma / Master Thesis

  • GRAND Decoders for 5G (Niklas Förster, 01/22 – 06/22)
  • Examination of Identification in Software Defined Radios (Alexander Hefele, 10/21 – 03/22)


Best Paper of the First International Workshop on Technologies for Network Twins (TNT), co-located with IEEE/IFIP NOMS 2022 Conference



von Lengerke, Caspar; Hefele, Alexander; Cabrera, Juan A.; Fitzek, Frank H. P.

Stopping the Data Flood: Post-Shannon Traffic Reduction in Digital-Twins Applications Inproceedings

In: NOMS 2022-2022, pp. 1-5, 2022, ISSN: 2374-9709.

Abstract | Links | BibTeX


Schmitz, Johannes; von Lengerke, Caspar; Airee, Nikita; Behboodi, Arash; Mathar, Rudolf

A deep learning wireless transceiver with fully learned modulation and synchronization Inproceedings

In: 2019 IEEE International Conference on Communications Workshops (ICC Workshops), pp. 1-6, IEEE 2019.