A space-based solution to connect remote regions is soon to become reality. But using low-orbiting satellites as telecommunications relay stations means certain functionalities of current terrestrial solutions have to be reinvented. Their constant movement is the reason. For the BPI 5G NTN mmWave project, Télécom Paris scientists are tackling this technical challenge, by developing new algorithms and performance models in order to assess the limitations of the system and then optimize it.

Neural networks are AI models designed by machine learning. They are inspired by the workings of the human brain and allow machines to carry out different tasks autonomously. Using large quantities of data as examples, they can be trained in image recognition or text analysis. Beyond their predictive performance, a number of scientific challenges still need to be resolved, concerning the understanding of their limits, reliability of their use, and their acceptability, in addition to ethical issues such as energy consumption. Stephan Clémençon, a researcher in artificial intelligence at Télécom Paris, explains more.

Following her first ERC grant in 2017, Michèle Wigger has been awarded a second European grant to support her work in information theory. The Telecom Paris researcher will continue to study the fundamental limits of communication systems, but will focus her main research efforts on the theoretical side.