CentraleSupélec

Des formations d’excellence de niveau international

LANEAS

 

RESEARCH TOPICS
 

Mathematical Tools in Large Dimensions

At the core of the LANEAS research are theoretical advances in large dimensional random matrix theory, free probabiliy theory, game theory and mean field games, stochastic geometry and point processes, communication/ information theory.
 

Antenna Array and Network Signal Processing

Applications of our theoretical tools are made in the discipline of signal processing for large antenna arrays, such as improved detection and localization schemes, robust estimation methods, estimation under stationary noise.
 

Data Mining

A growing activity on BigData is taking place in the LANEAS group, with in particular research in random matrix methods for machine learning and sparse principal component analysis, along with distributed storage and caching techniques in networks.
 

Wireless Networks

Multi-cellular multi-user multi-antenna are at the core of the application-oriented research in the LANEAS group, with the performance analysis, precoder design, and topology improvement of multicell massive MIMO, small cells, and heterogeneous networks for the design of 5G.

Find out all publications from LANEAS

 

 

TEACHING

The group has been actively providing courses in various academic institutions (all) around the world:
 

  • Inference Methods for Science and Engineering Applications (Master and PhD level: University of Oslo).
  • Statistical Signal Processing for Communications (Master level: Coltech, Vietnam).
  • Multi-Antenna Technologies (graduate level: ENSEIRB Bordeaux, Université of Avignon, Ecole Polytechnique de Tunisie).
  • Random Matrix Theory and its applications to Wireless Communications (Master and PhD level: University of Oslo, University of Aalborg, INRIA, CentraleSupélec, Orange-Labs, Cambridge University).
  • Game Theory and its applications to Wireless Communications (Master and PhD level: University of Oulu, University of Oslo, CentraleSupélec, University of Modena).
  • Channel Modelling (Master SAR at CentraleSupélec).
  • Theoretical Foundations of Mobile Flexible Networks (Master SAR: CentraleSupélec).

 

VIDEO

Professor Mérouane Debbah for a lecture dedicated to 5G:

Les dernières publications

Article dans une revue
05/07/2018
Communication dans un congrès
20/05/2018
Collaborative Artificial Intelligence (AI) for User-Cell Association in Ultra-Dense Cellular Systems
Kenza Hamidouche, Ali Taleb Zadeh Kasgari, Walid Saad, Mehdi Bennis, Merouane Debbah
Communication dans un congrès
15/04/2018
Achievable rate maximization by passive intelligent mirrors
Chongwen Huang, Alessio Zappone, Merouane Debbah, Chau Yuen
Article dans une revue
01/04/2018
The Power of Side-Information in Subgraph Detection
Arun Kadavankandy, Konstantin Avrachenkov, Laura Cottatellucci, Rajesh Sundaresan
Article dans une revue
01/04/2018
Optimal Design of the Adaptive Normalized Matched Filter Detector
Abla Kammoun, Romain Couillet, Frédéric Pascal, Mohamed-Slim Alouini
Voir toutes les publications du laboratoire sur HAL