Talk: Prof. Giuseppe Durisi (July 05, 2019 at 1:15 PM, LNT Seminar room N2408)
On July 05, 2019 at 1:15 PM, Prof. Giuseppe Durisi from Chalmers University will be giving a talk in the LNT Seminar room N2408 about "Short-packet communications - fundamentals and practical coding schemes".
Short-packet communications - fundamentals and practical coding schemes
Prof. Giuseppe Durisi
Chalmers University of Technology
The design of block codes for short information blocks (e.g., a thousand or less information bits) is an open research problem that is gaining increasing relevance because of emerging applications in the area of lowlatency wireless communication. In this lecture, I shall review the fundamental tradeoff between throughput and reliability when transmitting short packets, using recently-developed tools in ﬁnite-blocklength information theory. I will then illustrate how to use the bounds to benchmark the performance of actual short-packet coding schemes.
Giuseppe Durisi received the Laurea degree summa cum laude and the Doctor degree both from Politecnico di Torino, Italy, in 2001 and 2006, respectively. From 2006 to 2010 he was a postdoctoral researcher at ETH Zurich, Zurich, Switzerland. In 2010, he joined Chalmers University of Technology, Gothenburg, Sweden, where he is now professor with the Communication Systems Group and co-director of Chalmers ICT Area of Advance and Chalmers AI research centre.
Dr. Durisi is a senior member of the IEEE. He is the recipient of the 2013 IEEE ComSoc Best Young Researcher Award for the Europe, Middle East, and Africa Region, and is co-author of a paper that won a “student paper award" at the 2012 International Symposium on Information Theory, and of a paper that won the 2013 IEEE Sweden VTCOM-IT joint chapter best student conference paper award. In 2015, he joined the editorial board of the IEEE Transactions on Communications as associate editor. From 2011 to 2014, he served as publications editor for the IEEE Transactions on Information Theory. His research interests are in the areas of communication and information theory and machine learning.