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).