MAchine learning-driven Terahertz-enabled Reconfigurable Intelligent Surface-based 6G networks MATRIS

Project: MAchine learning-driven Terahertz-enabled Reconfigurable Intelligent Surface-based 6G networks

Acronym: MATRIS

Main Objective:
(1) Advanced channel and network modelling of Reconfigurable Intelligent Surface (RIS)-based 6G networks;
(2) ML-driven network optimization in dual-mobility and multi-connectivity RIS networks; (3) Cross-layer optimization for enhanced spectral, energy and computational efficiencies.

Reference: 2022.07313.PTDC

Funding: FCT/PTDC

Start Date: 12-03-2023

End Date: 11-08-2024

Team: Sherif Adeshina Busari, Joaquim Manuel Camões Sobral de Bastos, Jonathan Rodriguez Gonzalez, Karamot Kehinde Biliaminu, Hemalatha Vulchi

Groups: Mobile Systems - Av

Partners: Mobile Systems - Av

Local Coordinator: Sherif Adeshina Busari

United Nations Strategic Development Goal - Industry, Innovation and Infrastructure

Associated Publications

1Papers in Conferences
K. B. Biliaminu, S. A. Busari, J. B. Bastos, J. Rodriguez, Impacts of Dataset and Codebook Sizes on ML-Driven Beam Prediction for mmWave V2I Communication, WINCOM, Leeds, United Kingdom, July, 2024,
| Abstract | Full text (PDF 1 MB) | BibTex

Project / MATRIS

Project: MAchine learning-driven Terahertz-enabled Reconfigurable Intelligent Surface-based 6G networks