🔬 Researchers
OLIVA DELGADO, ANTONIO DE LA
Principal Researcher
AZCORRA SALOÑA, ARTURO
Researcher
BERNARDOS CANO, CARLOS JESUS
Researcher
ALMODOVAR HERREROS, JONATHAN
Researcher
GROSHEV, MILAN
Researcher
RICO MENÉNDEZ, DAVID
Researcher
BARROSO FERNANDEZ, CARLOS
Researcher
PICAZO MARTINEZ, PABLO
Researcher
CONSTANTINE OCHIENG, AYIMBA
Researcher
CALVILLO FERNANDEZ, ALEJANDRO
Researcher
ZAHIR RODRIGUEZ, ADAM
Researcher
Project Type
European Research Project
Date/Time Interval
January 1, 2023 – June 30, 2025
Funding Entity
EUROPEAN COMMISSION RESEARCH EXECUTIVE AGENCY
Project Website
Abstract
6G is envisioned to accelerate the path started in 5G for catering to the needs of a wide variety of vertical use cases, both current and emerging. This will require major enhancements of the current 5G capabilities especially in terms of bandwidth, latency, reliability, security, and energy. PREDICT-6G’s mission is therefore set towards the development of an end-to-end 6G (E2E) solution including architecture and protocols that can guarantee seamless provisioning of services for vertical use cases requiring extremely tight timing and reliability constraints. To succeed, the solution will target determinism network infrastructures at large, including wired and wireless segments and their interconnections. PREDICT-6G will develop a novel Multi-technology Multi-domain Data-Plane (MDP) overhauling the reliability and time sensitiveness design features existing in current wired and wireless standards. The ambition is for the MDP design to be inherently deterministic. To achieve this, PREDICT-6G will develop an AI-driven Multi-stakeholder Inter-domain Control-Plane (AICP) for the provisioning of deterministic network paths to support time sensitive services as requested by end-customers and with different scaling ambitions, e.g., from the network in a single vehicle to a large, geographically dispersed network. This requires timely monitoring and prediction of the behavior of the complete network, including identifying potential sources of quality violations and analyzing various routes of the traffic flows. These capabilities will be delivered through the PREDICT-6G AI-powered Digital Twin (DT) framework, allowing the prediction of the behavior of the end-to-end network infrastructure, and enabling anticipative control and validation of the network provisions to meet the real-world time-sensitive and reliability requirements of the running services.
