General information

GENerative and connected intelligence for 6G Open ManagemEnt (GENOME) research and training programme aims at investigating, developing/fine-tuning and validating large language models (LLMs) for the autonomous management and orchestration of various network technological domains (O-RAN, edge, cloud) through intent-based networking and task-agnostic network functions. It also targets the establishment of a connected intelligence framework for the coordination between these functions via on-the-fly protocol learning to mitigate conflicting management decisions and maximize utilization. Network configuration will also be generated automatically through innovative neuro-symbolic AI algorithms. Moreover, the transparency and resilience of the AI models is researched. All the developed components will be validated via both simulation and testbed experiments, and integrated into a final proof-of-concept. Besides, a detailed training plan is designed including schools, industrial days and soft-skills courses. It involves industrial partners to ensure that career perspectives of ESRs will be significantly increased by participation in the project. High quality dissemination and exploitation activities are also considered.

Objective Connectivity is the major driver in the modern “information society”, where the range of data-driven applications is exploding, and new information-based value chains are rapidly emerging. Optical networks are the backbone of the global communication infrastructure, interconnecting billions of people and a huge number of various autonomous devices, control systems, and machines. Optical systems’ development incites the skyrocketing growth in the demand for data exchange and harnessing, fuelled by web-based services such as ultra-HD streaming, cloud services, 5G proliferation, fostering the changes in the digital world, and shaping the structure of the modern society. The demand growth is especially pronounced in the access and metro links, where data rates largely exceeding the current <1 Tb/s will be required. Moreover, the COVID-19 – with the huge number of people working from home – has intensified the pressure on the optical networks. Also, features such as the financial cost of the system elements, latency, dynamic reconfigurability, and energy consumption gain progressively more importance for the new generation of access and metro networks. The Doctorate Network NESTOR will answer the How? When? and Where? coherent optical transceiver will be deployed in metro-aggregation optical networks to meet the demand for new cost-efficient solutions. NESTOR will also address the Who? by providing advanced training to 10 Fellows - from a new generation of engineers - with PhD projects significantly expanding the flexibility and capacity of access/metro networks. NESTOR will provide Fellows with a uniquely broad education ranging from recent advances in ML&AI to real-world telecom engineering, which will enable them to design and implement high-capacity access and metro networks.

The 6G-EWOC project aims to contribute to the development of future 6G-AI based networks by ending with TRL-4-level developments on critical technologies and devices for expanding the reach of 6G, especially in high mobility scenarios. It is addressing Key Societal Value indicators (KVI) defined by the Work Programme and developing KV enablers such as services for coordination, precise positioning and localization, multi-agent supporting network architecture and joint communication and sensing. The three ambitions of 6G-EWOC focus on: AMB1, Optical Wireless Communications (OWC) for V2V and high-rate (Gb/s) V2I applications, chip-scale optical beamformers, and developing connected laser/radio detection, ranging, and communication (Lidar/Radar). AMB2, PIC and ASIC for tuneable transmitter and receiver concepts for fiber-based fronthaul supporting 50 Gbps and 100 Gbps per wavelength over DWDM fiber links and SDN-enabled photonic switching. AMB3 focuses on AI-assisted control and orchestration of resources for the multi-band, heterogeneous 6G-EWOC network concept and AI-based applications development for autonomous vehicles. Up to 17 KPIs are expected to be validated at three final demonstrations. In conclusion, 6G-EWOC search to develop an AI-enhanced fibre-wireless optical 6G network in support of connected mobility by creating a new access network for high mobility scenarios and expanding the reach of 6G through the integration of optical and wireless technologies, free space optics, and joint communication and sensing. It is supported by a fast, reconfigurable, highly dynamic, and customizable optical fiber fronthaul infrastructure, minimizing optoelectronic transitions by tuneable and programmable devices and low energy photonic switching of (packet/optical) spectrum and spatial resources, controlled by AI-based SDN. Providing end-to-end connectivity between AI-based edge computation units supporting connected mobility in a fast reconfigurable network architecture.