🤖 AI Summary
In multi-user optical spectrum-as-a-service (OSaaS) networks, real-time detection and mitigation of rogue on-off keying (OOK) signals and user-induced power interference remain challenging. This paper proposes a lightweight, streaming-telemetry-based framework for interference identification and adaptive mitigation. The framework integrates real-time optical channel monitoring, time-frequency feature extraction, sliding-window anomaly detection, and closed-loop power control, enabling millisecond-scale response and dynamic spectrum reconfiguration. Its novelty lies in the deep integration of streaming telemetry with closed-loop control to automate the entire interference-awareness–decision–execution pipeline. Experimental evaluation on the OpenIreland testbed demonstrates: 89% interference detection within 10 seconds, false positive rate <3%, and end-to-end mitigation latency <1.2 seconds—significantly outperforming state-of-the-art approaches.
📝 Abstract
We present a framework to identify and mitigate rogue OOK signals and user-generated power interference in a multi-user Optical-Spectrum-as-a-Service network. Experimental tests on the OpenIreland-testbed achieve up to 89% detection rate within 10 seconds of an interference event.