Mobile Communications

Prof. Markus Rupp is leading the research group on mobile communications at the ITC. In the broad field of mobile communications our group focuses on three main topics within the scope of next generation mobile cellular networks: link layer measurements and simulations, traffic analysis and simulation at the IP layer and cross-layer optimizations.

Mobile Comm Draft

Multimedia Systems

Research in this field is about multimedia signal processing for big data and multimedia transmission in wireless networks under Quality-of-Service (QoS) constraints specific to the applications.

On the signal processing side, the work particularly involves advanced methods for big data such as compressed sensing, iterative recovery algorithms and sparse model selection -- a variety of machine learning -- with applications, e.g., in image processing and communications.

For multimedia transmission topics include multiuser information theory, flexible and powerful channel codes that can be decoded efficiently, code designs for multihop applications such as “relaying”, practical schemes for joint source-channel coding, signal processing algorithms for user interfaces as well as Cross-Layer design for multiuser systems. The goal is to optimise the overall system performance while efficient use is made of the resources (bandwidth, power, complexity) and the QoS demands of the users’ applications are met.

Communication Networks

The main research field of the communication networks group is network security. The groups works on network supervision methods and network forensics with a focus on malware communication in IPv4 and IPv6 networks. This also includes research on network steganography and the detection of covert channels in TCP/IP traffic. One application field is the secure communication in cyber-physical systems such as smart grids or smart production environments.

Signal Processing

A major focus of our research is statistical signal processing in wireless sensor networks. We pursue a fully distributed (decentralized, cooperative) approach that does not require a central processing unit. Our goal is to estimate, detect, or classify certain global or local states using only local processing at the individual sensor nodes and local wireless communications between neighboring sensor nodes. An example is the task of detecting moving objects such as vehicles or robots and estimating their locations and velocities, using spatially distributed sensors that sense acoustic or radio signals emitted by these objects.

Communication Theory

The research of the communication theory group deals with physical layer aspects of wireless networks, efficient transceiver design, network information theory, distributed algorithms for statistical inference, and signal processing on graphs for big data.