• Home
  • TU Dresden
  • Fakultät Elektrotechnik und Informationstechnik
  • Caspar von Lengerke
Caspar von Lengerke

Caspar von Lengerke
TU Dresden | TUD · Fakultät Elektrotechnik und Informationstechnik

Master of Science

About

9
Publications
403
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
54
Citations
Additional affiliations
April 2018 - January 2019
RWTH Aachen University
Position
  • Master Thesis
Education
April 2017 - September 2019
RWTH Aachen University
Field of study
  • Electrical Engineering
October 2013 - March 2017
RWTH Aachen University
Field of study
  • Electrical Engineering

Publications

Publications (9)
Article
Identification via channels (ID) is a goal-oriented (Post-Shannon) communications paradigm that verifies the matching of message (identity) pairs at source and sink. To date, ID research has focused on the upper bound λ for the probability of a false-positive (FP) identity match, mainly through ID tagging codes that represent the identities through...
Preprint
Full-text available
This paper provides an overview of the hardware and software components used in our test bed project the NET Playground. All source information is stored in the GitLab repository (https://gitlab.com/Paulteck/net-playground). In the Hardware section, we present sketches and 3D views of mechanical parts and technical drawings of printed boards. The S...
Article
Full-text available
A wide range of information technology applications require the identification of a particular message or label that represents the identity of an object at a distance, e.g., over a wireless channel. Conventionally, the underlying information that represents the identity is transmitted over the channel, following the information-theoretic concept o...
Preprint
Full-text available
In this paper, we present a deep learning based wireless transceiver. We describe in detail the corresponding artificial neural network architecture, the training process, and report on excessive over-the-air measurement results. We employ the end-to-end training approach with an autoencoder model that includes a channel model in the middle layers...

Network

Cited By