In ALLEGRO, we’ve been diving deep into innovative methods to enhance pre-tilt power optimization and improve AI-driven GSNR and LP QoT estimation. Our latest study demonstrates how solving interrelated inverse differential equations can optimize pre-tilt power, achieving:
✅ Fast computation – Optimal power levels per span in just seconds
✅ Enhanced GSNR – Boosting average channel GSNR by up to 0.5 dB
✅ Maximized span capacity – Ensuring a uniform OSNR while mitigating Interchannel SRS (ISRS) effects
🔍 Key Findings:
📌 Pre-tilt power strategies outperform uniform launch power in terms of span capacity and OSNR uniformity
📌 A 0.5 dB GSNR improvement per span enables up to 30% of LPs to upgrade to higher modulation formats
📌 Implementing optical gain equalizers in ROADMs and inline amplifiers balances the trade-off between performance gains and economic feasibility
As the industry pushes toward more efficient optical networks, these advancements in power optimization and AI-driven models mark an important step forward. Exciting times ahead!
📢 What are your thoughts on leveraging AI for smarter optical network design? Let’s discuss!
#OpticalNetworking #AI #QoT #ALLEGRO #Innovation
