Federated O-RAN Slice SLA Prediction: A Cross-Architecture Empirical Benchmark on Colosseum/ColO-RAN

Federated learning (FL) on O-RAN edge gNBs is a natural candidate for slice-level SLA-violation forecasting when raw per-user telemetry is undesirable or infeasible to pool centrally (FL itself does not provide formal privacy guarantees; see Section 8 L16). Yet the deployment design space — sequence backbone, federation algorithm, client-heterogeneity partition, commodity edge hardware — has been studied one axis at a time, leaving the joint behaviour under realistic O-RAN traffic characterised