Random Matrices in Communications and Signal Processing



Zeit/Ort n.V.:

  • Di 10:15-11:45, Raum E 1.12
  • Fr 14:15-15:45, Raum E 1.12
  • Einzeltermin am 01.02.2019 14:15-15:45, Raum 05.025

Studienfächer / Studienrichtungen

  • WF ASC-MA ab Sem. 1
  • WF CME-MA ab Sem. 2
  • WF EEI-MA-INT ab Sem. 2

Prerequisites / Organizational information

Recommended: Good skills in linear algebra, probability theory and complex analysis


Dual antenna arrays, compressive sensing, Wishart distribution, factor iid model, Kronecker model, convergence of random variables, semi-circle law, quarter circle law, full circle law, Haar distribution, Marchenko-Pastur distribution, Stieltjes transform, Girko’s law, unitary invariance, freeness, free convolution, R-transform, free central limit theorem, free Poisson limit theorem, subordination, S-transform, R-diagonal random matrices, R-diagonal free convolution, Haagerup-Larsen law, operator-valued freeness, linearization of noncommutative polynomials, free Fourier transform, self-averaging properties, microscopic vs. macroscopic random variables, quenched random variable, a statistical physics point of view of digital systems, spin glasses, frozen disorder, replica method, replica continuity, replica symmetry, replica symmetry breaking, approximate message passing, classification of np-complete problems

Empfohlene Literatur

- Mingo, J., Speicher, R.: Free Probability and Random Matrices, Springer, 2017 - Couillet, R., Debbah, M.: Random Matrix Methods for Wireless Communications, Cambridge Univ. Press, Cambridge, 2011. - Mezard, M., Montanari, A.: Information, Physics, and Computation, Oxford Graduate Texts, 2009.

Zusätzliche Informationen

Erwartete Teilnehmerzahl: 20