Communication Theory

Welcome at the Communication Theory Group at the Institute of Communications Engineering. We are doing teaching and research in various fields of reliable, secure, and efficient communications.

Tasks and Challenges in Communications

Communication, from an engineering point of view, is the activity of conveying information. Thereby, messages can be communicated across the space (i.e., from one location to an other—telecommunications) or across the time (i.e., from one time instant to an other—storage).

Of course, communication should be done as efficient as possible. The limited resources (power, bandwidth, processing capabilities, ...) should be utilized in the most gentle way. The most important optimality criteria in Digital Communications are

  • Power Efficiency
  • Bandwidth Efficiency
  • Complexity
  • Latency

New Challenges in Communications

The current challenges in Digital Communications are multifaceted. Ever increasing data rates and ubiquitous communications (every body at every time at every place) put demanding challenges on the design of future communication systems. In particular, the following topics are currently addressed in several research projects at our group:

  • Interference
    • In multiuser systems a number of users share a common medium, hence multiple access schemes are required.
    • In multiantenna systems antenna arrays at transmitter and receiver are used. The mutual interference has to be handled via some equalization schemes for MIMO systems.
  • Nonlinearities
    • At practical implementations, clipping at power amplifiers takes place. For modulation formats (in particular OFDM) with high peak-to-average power ratio (PAR) of the transmit signal, PAR reduction schemes have to be designed.
    • In some applications (typically fiber-optical communications) the channel itself has nonlinear behaviour. For such channels, suited modulation formats and adapted coding schemes are required.
  • Signals with Structure
    • In a number of applications, sparse signals, i.e., signals where only a few components (in signal space) are active, are inherently present. For efficient processing, this structure has to be taken into account, e.g. by means of techniques from compressed sensing.
    • Such structure can also be attractive in the design of modulation formats, e.g., via a restriction to low-dimensional signal spaces are via some discrete-valued constraint. Here, suited estimation algorithms are called for.
  • No Channel Knowledge
    • In a number of applications no channel state information (CSI) is available (neither at transmitter nor receiver). The use of non-coherent transmission schemes can circumvent this problem. Typical applications are ultra-wideband communications (UWB) and so-called massive MIMO systems.
    • Via channel transformation the characteristics of the channel may be beneficially be modified. E.g., using differential detection strategies unknown "offsets" may be eliminated.

Current Working Areas

Based on the above challenges, the current projects (selection) are

  • The interrelations between channel coding and precoding for broadcast channels and in network coding
    (funded by DFG within the priority programme COIN)
  • Design of adaptive modulation and coding for flexible and secure optical networks
    (funded by BMBF within the project ADVAntage-Net/SASER)
  • The theory of discrete sparse signals and efficient recovery algorithms
  • Noncoherent detection in massive MIMO systems
  • Capacity of peak-limited channels and algorithms for approaching it
  • Peak-power reduction algorithms for OFDM

Open Theses

We consistently offer Bachelor and Master Theses in the above research fields. Please have a look at current topics.