Signal and Information Processing in Science and Engineering - Information Networks

02.06.2008 - 31.05.2011
Forschungsförderungsprojekt
The research in this project is split into three Work Packages (WPs): WP 6.1 deals with Shannon theoretical analysis of information flows in communication networks, ranging from three-node relay networks up to large networks with several thousands of nodes. Specific emphasis is on scale-free networks with power-law degree distribution. Here, the idea is to study asymptotic capacity scaling in this type of networks and to understand the impact of network topology, node failure, and communication protocols on the achievable data rates. WP 6.2 is concerned with the performance limits of multi-terminal inference in small and large networks. Inference networks differ from communication network in that reliable distributed detection and estimation can often be achieved even if reliable communication at non-zero rate is not possible. Finally, WP 6.3 applies ideas and methods from the theory of graphical models to the development of powerful communication and inference strategies for such networks (including multi-terminal source-channel coding, joint channel and network coding, and cooperative communications) and to the design of iterative distributed inference algorithms that perform inference by propagating messages back and forth through the network (distributed belief propagation, gossip algorithms, etc.).

Personen

Projektleiter_in

Projektmitarbeiter_innen

Institut

Grant funds

  • FWF - Österr. Wissenschaftsfonds (National) Austrian Science Fund (FWF)

Forschungsschwerpunkte

  • Distributed and Parallel Systems: 30%
  • Telecommunication: 40%
  • Sensor Systems: 30%

Schlagwörter

DeutschEnglisch
Wireless networksFunknetze
Distributed signal processingverteilte Signalverarbeitung
Cooperative communicationsKooperative Kommunikation
Scale-free networksSkalenfreie Netze

Publikationen