Lab: Design a closed-loop optimization system — twin + AI + RIC + action

Lab Scenario: Closed-Loop Mobility Optimization

In this lab you design a complete closed-loop system for mobility optimization in a multi-vendor O-RAN deployment. The target network has 200 cells across three vendors with frequent handover failures at cluster boundaries. Your system must detect mobility problems from live KPIs, simulate parameter changes in a digital twin, use AI to recommend optimal handover thresholds, deploy validated changes through the near-RT RIC via E2 interface, and monitor outcomes for automatic rollback if needed. The design must operate at L3 autonomy with human approval gates for the first month before…