Research: Chair of Communications Engineering

Coding and Modulation

Efficient communication requires higher order modulation and error control codes. We are approaching the theoretical limits by implementing Shannon‘s blueprint. Two key concepts are probabilistic shaping and quantized message passing to reduce transmitter power and receiver complexity. We design and implement state-of-the-art low-density parity-check (LDPC) and polar codes and decoders over binary and non-binary fields. We test our prototypes in close collaboration with industry.

Currently working in this area:

  • Emna Ben Yacoub
  • Mustafa Coşkun
  • Delcho Donev
  • Tobias Prinz
  • Yusuf Şener
  • Thomas Wiegart
  • Peihong Yuan

Information Theory for Machine Learning, Security, and Identification

We are developing information theoretic frameworks, codes, and algorithms for signal processing problems such as machine learning and compressed sensing. As the need for secure communications increases, we concentrate on privacy and secrecy related topics. We further investigate non-standard topics such as information theory and codes for identification

Currently working in this area:

  • Christian Deppe
  • Abdalla Ibrahim
  • Diego Lentner
  • Mohammad Salariseddigh
  • Volodya Sidorenko

Wireless and Optical Communications

Two key technologies to increase data rates are multi-input, multi-output (MIMO) and space-division multiplexing (SDM). For wireless, massive MIMO uses hundreds of antennas with simplified signal processing, and joint communications and sensing enables efficient internode communication and control. For optical fiber, waveform propagation is described by a non-linear Schrödinger equation (NLSE) and receiver performance can be improved by machine learning algorithms. We are further studying information theory for quantum communications.

Currently working in this area:

  • Christian Deppe
  • Francesca Diedolo
  • Javier Garcia
  • Mari Kobayashi
  • Mohammad Mahvari
  • Tayyab Mehmood
  • Uzi Pereg