Tutorial on Random Matrix Theory for Signal Processing Applications

[19 Dec. 2011] In the description and analysis of systems with many users and multiple antennas for broadcast and reception (multiple input, multiple output, or MIMO, systems), researchers and developers in the field of telecommunications are confronted with multi-dimensional stochastic problems. In his tutorial at ACCM, Dr. Romain Couillet of École Supérieure d'Électricité (Supélec) of Paris introduced methods to handle such stochastic problems.

Couillet’s tutorial on “Random matrix theory for signal processing applications” provided an introduction to the most important tools of Random Matrix Theory. He demonstrated application of these tools in the field of wireless communication and signal processing, including examples for capacity estimation in complex communication networks and improved signal detection and estimation. More than 20 participants from Linz, Vienna and Klagenfurt attended the tutorial.

Couillet is assistant professor at the Institute for Systems Sciences and the Energy Challenge at Supélec. His research foci are information theory, signal processing, complex systems and random matrix theory. In 2008 he was distinguished with the Valuetools Best Student Paper Award and in 2011 with the EEA/GdR ISIS/GRETSI Best PhD Thesis Award.
Couillet held his tutorial at ACCM on invitation of Univ. Prof. Dr. Andreas Springer, coordinator of the area Wireless Technologies at ACCM and head of the Institute for Telecommunications and High-Frequency Systems at JKU.

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