AI-empowered Multimodal Communications with MEC Optimization (MUSE-COM^2)
Semantic communications, Multimodal Generative Models, Information Theory, Information decomposition, Wireless communications, Distributed optimization
Project description
The project aims to develop and validate AI-empowered multimodal communications, considering the semantics of individual modalities jointly optimized with the processing of modalities in multi-access edge computing (MEC) servers. Unlike conventional semantic and goal-oriented communications, the inclusion of information processing in MEC imposes new challenges related to the impact of information carried in individual modalities on the MEC processing outcome. The goal is to obtain a coherent framework jointly reducing the amount of information carried over the wireless links and subsequently processed in MEC; thus, saving not only radio and computing resources, but also energy while leading to the same outcome of the MEC processing.
The project consortium encompasses four partners (Czech Technical University in Prague, EURECOM, University of Oulu, Robert Bosch spol s r.o.) from three countries (Czech Republic, France, Finland).
People involved
- Pietro Michiardi
- Giulio Franzese
- Alberto Foresti
- Mustapha Bounoua
Funding
- CHIST-ERA Call 2022 in frame of Horizon Europe Future and Emerging Technologies (FET) programme of the European Union through the ERA-NET Cofund.
- Technology Agency of the Czech Republic under the program Epsilon
- French National Research Agency
- Research Council of Finland
- Funding of Czech partners by EU under the National Recovery Plan (Recovery and Resilience Facility)