ESR10. Fabio Maresca

Short biography

I am Fabio Maresca, a 26 years old Italian guy who joined NEC Laboratories Europe (Heidelberg, Germany) in January 2022. Here I work as the ESR 10 for the "5GSmartFact" European project, and my position expects the deployment of 5G networks that target the IIoT requirements in factory environments.

I graduated in computer engineering (MSc) at the University of Naples Federico II in December 2021, my background involves mainly computer networking, plus a little contamination of telecommunications and machine learning (just some classes and curiosity). In February 2022 I enrolled in the Network Engineering PhD at UPC (Universitat Politécnica de Catalunya) which will start in the next weeks.

Short description of project objectives

The project objectives are to propose a smart orchestration of IT computational resources among different IT (edge) platforms; this will be accomplished by performing scaling-up/down/migration operations. Real MEC platforms available at NEC laboratories will be exploited. In this regard, my research activity has been addressed toward two works so far: (I) the deployment of Reconfigurable Intelligent Surfaces (RIS) in industrial environments, and (II) the realization of a specific scenario that involves MEC technologies. As for the former, I studied the state of the art related to RIS and submitted a paper to the SPAWC 2022 conference (23rd IEEE International Workshop on Signal Processing Advances in Wireless Communications”). The work titled “A Frequency-Agnostic RIS-based solution to control the Smart Radio Propagation Environment” proposes the idea of a reconfigurable RIS by leveraging reconfigurable patch-antennas and, moreover, it proposes an optimization algorithm to mitigate the negative effects of mutual coupling. These have been validated with the CST Studio Suite simulation tool. The latter (II) is a work in progress that aims to share information from autonomous vehicles thanks to MEC technologies, in order to classify each type of vehicle on the edge nodes depending on the information collected.