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).
Projects
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