The Foundations & Algorithms Group

Introduction

Within the Communication Systems  Department of EURECOM, the Foundations and Algorithms group aims at a multi-disciplinary field of research for better understanding of the fundamental performance limits of all kinds of communications systems and the proposal of new algorithmic methods to approach these limits or sometimes to push them further.  Our research lies at the cross-roads of information theory, coding, statistics, signal processing, learning theory, and applied mathematics.

These days we resort to a range of tools which include (not limited to):

• Linear algebra
• Probability theory
• Game and decision theory
• Coding theory
• Optimization
• Estimation and detection
• Random matrix and large system theory
• (machine) learning
• Multi-agent decision theory

The Applications 

Applications of our research are many fold, with a basic constituent being a source of information that needs to be communicated safely and quickly to a destination or stored efficiently. Multi-terminal communication theory relates to the case of multiple sources or destinations (such as many wireless user terminals trying to communicate simultaneously in a mobile network). We also consider the problem of efficient treatment (e.g. via caching) of "popular" data in a network, such as movies which are expected to be request by the large number of users  within a limited period of time.

The Research Trends

Below is depicted a panorama of the hottest research trends within communications theory for wireless networks, and addressed by our group:

• Small Cells

  • Dense, low power, full reuse networks
  • Massively cooperating wireless networks

• Distributed decision for wireless networks

  • Distributed precoding/decoding for MIMO
  • Distributed interference management under limited feedback
  • Fundamental limits of communications under decentralized information
  • Robust multi-agent decision under uncertainties

• Localization vs. communication

  • Emerging terminal localization techniques
  • Localization-aided communications and services

• Energy harvesting networks

  • Optimization of wireless network with energy harvesting nodes
  • Wireless power transfer

• Radio access  in the cloud

  • In network processing
  • Local versus global radio cooperation

• Radio edge caching

  • Uncoded and coded caching peformance limits
  • Joint design of communications and caching policies

• Wireless Robotics and AI

  • Machine learning for (decentralized) network optimization
  • Learning for flying radio access networks (UAV-aided networks)