Programmable Reconfigurable Optical Transport for Efficiently offering Unconstrained Services in 6G

Informazioni relative al progetto

PROTEUS-6G

ID dell’accordo di sovvenzione: 101139134

DOI

10.3030/101139134

Data della firma CE 8 Dicembre 2023

Data di avvio 1 Gennaio 2024

Data di completamento 31 Dicembre 2026

Finanziato da

• Digital, Industry and Space

Costo totale

€ 4 182 601,25

Contributo UE

€ 3 953 174,00

Coordinato da

PANEPISTIMIO PATRON
Greece

Periodic Reporting for period 1 - PROTEUS-6G (Programmable Reconfigurable Optical Transport for Efficiently offering Unconstrained Services in 6G)

Periodo di rendicontazione: 2024-01-01 al 2025-06-30

Sintesi del contesto e degli obiettivi generali del progetto

PROTEUS-6G addresses the fundamental challenge of developing programmable packet-optical transport infrastructure capable of supporting 6G networks' stringent requirements for ultra-high capacity (6.4 Tb/s per fiber), sub-millisecond latency, and enhanced energy efficiency. The project targets two critical scenarios: dynamic functional splits enabling adaptive RAN configurations from split option 1 to 7.2 for flexible resource allocation, and cell-free massive MIMO connectivity supporting split option 8 for advanced distributed antenna processing. Through coordinated development of spatially-diverse point-to-multipoint (SDPtMP) optical distribution networks, lite-coherent transceivers with all-optical signal processing, and intelligent SDN-based orchestration systems, PROTEUS-6G aims to enable flexible, scalable fronthaul and midhaul networks that can dynamically adapt to varying traffic demands and service requirements. This comprehensive approach positions Europe at the forefront of 6G optical networking technology while supporting the transition toward more sustainable, energy-efficient telecommunications infrastructure

Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti

Over the first 18 months, PROTEUS-6G has achieved substantial progress across all technical work packages while maintaining strong consortium collaboration and budget alignment. WP2 successfully completed 6G x-haul requirements definition and network architecture specifications, WP3 advanced SDPtMP component development including silicon nitride PIC fabrication and characterization with dual-stage RAMZI interleavers achieving 28 GHz bandwidth and 20 dB extinction, and WP4 delivered significant milestones including 800 Gb/s plasmonic transmitter prototypes with sub-1V drive voltages and 200 GHz electro-optic bandwidth. WP5 implemented multi-layer SDN orchestration frameworks with telemetry-adapted protocols and autonomous networking capabilities, while the consortium conducted six successful plenary meetings across Europe and published 15+ peer-reviewed conference papers and 3+ journal articles. Strong dissemination activities include active social media engagement (454+ LinkedIn followers), comprehensive project website maintenance (5,700+ page views), and preparation for WP6 integration demonstrations targeting validation of capacity, latency, and energy efficiency KPIs

Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)

PROTEUS-6G has demonstrated significant advances in packet-optical transport technologies that extend beyond current 5G capabilities. The project has successfully developed spatially-diverse point-to-multipoint (SDPtMP) architectures using silicon nitride photonic integrated circuits with dual-stage RAMZI interleavers, achieving four-port subcarrier distribution with enhanced spectral efficiency while maintaining theoretical lossless operation. The innovative lite-coherent transceivers featuring all-optical signal processing (AOSP) have achieved 0.8 Tb/s per wavelength capacity with over 50% power reduction compared to conventional coherent systems, enabling 6.4 Tb/s aggregate capacity across 8 wavelengths in C/L bands. Additionally, the AI-driven network orchestration using lightweight deep CNN models has demonstrated 2× throughput gains and up to 10× energy savings under low-to-moderate loads, with multi-layer SDN frameworks enabling dynamic functional splits from option 1 to 8 with sub-second reconfiguration decisions

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