Communication Theory

The actvities in this area are centered about the following topics:

Physical layer aspects of wireless networks: interference management, relaying, PHY layer network coding

Efficient transceiver design: quantized message passing receivers, linear transceivers with feedback, MIMO detection and precoding, multicarrier systems

Network information theory: distributed source coding, information bottleneck principle, information-theoretic clustering

Distributed algorithms for statistical inference: consensus algorithms, distributed field reconstruction, decentralized detection

Signal processing on graphs: sampling and denoising of graph signals, probabilistic graphical models, graph learning and clustering

Our results are practically relevant for next-generation cellular systems, for sensor networks, and for big data applications (e.g., genomics, social media, recommender systems).


Ongoing Projects:

UNFOLD – Unleashing Finite-Alphabet Implementations of LDPC Decoders, WWTF Grant NXT17-013

Co3-iGrab – Communication and Complexity Constrained Inference over Graphs in Big Data, WWTF Grant ICT15-119

TINCOIN – The Information Bottleneck Method in Multiterminal Communication and Inference, WWTF Grant ICT12-054

Completed Projects:

NEWCOM# – Network of Excellence in Wireless Communications#

HIATUS – Enhanced Interference Alignment Techniques for Unprecedented Spectral Efficiency

DIP-WSN – Distributed Information Processing for Spatio-Temporal Fields in Wireless Sensor Networks

SISE/InfoNets – Signal and Information Processing in Science and Engineering/Information Networks

NEWCOM++ – Network of Excellence in Wireless Communications++

MASCOT – Multiple Access Space-time COding Testbed