With the aspiration to transform the current (5G) wireless thinking from focusing on “local” network improvements (e.g. isolating the radio access level or the resources management level etc.), to realizing a longer term vision of pervasive mobile virtual services, through a network managing computing and connectivity functions in an integrated way, ARIADNE envisions to bring together a novel high frequency advanced radio architecture and an Artificial Intelligence network processing and management approach in a unified system beyond 5G concept.
ARIADNE will investigate, theoretically analyse, design, develop, and showcase in a proof of concept demonstrator, an innovative wireless communications concept addressing networks beyond 5G, in which ultra-high spectral efficient and reliable communications in the bandwidth-rich D-band can be dynamically established and reconfigured by Machine Learning based design and intelligent network management, in both “Line of Sight” (LOS) and “Non-Line of Sight” (NLOS) environments.
The ARIADNE Pillars
- The ARIADNE project will develop new radio technologies for communications using the above 100GHz D-Band frequency ranges.
- ARIADNE will exploit the opportunities emerging for advanced connectivity based on metasurfaces where objects in the environment can become tuneable reflectors for shaping the propagation environment in D-band.
- ARIADNE will employ Machine Learning and Artificial Intelligence techniques to management necessary for high-frequency communications together with dynamic assignment and reconfiguration of the metasurfaces, so as to provide continuous and reliable high-bandwidth connections in the Beyond-5G scenario.
- Experimentally validate on software and hardware the theoretical findings and technological developments,
- Qualitatively and quantitatively assess the practical limitations and obstacles of AI-aided D-band communication systems in a real-life operating environment,
- Assess the feasibility of the proposed architecture and individual components/functionalities integration, and
- Identify possible accelerators for the adoption of AI-aided D-band wireless in the roadmaps of systems beyond 5G and potential limitations that may consist showstoppers and ways to overcome the associated obstacles.
ARIADNE objectives and Vision