Twin-Fidelity-Aware Resolution of Direct xApp Conflicts in Open RAN

2026-07-24

AI Summary

This work addresses the conflict between energy-saving and coverage/throughput-oriented xApps in Open RAN regarding downlink power configuration by proposing a lightweight, training-free arbitration mechanism that requires no prior knowledge of optimal policies. The approach employs a dual-fidelity-aware hard-switching strategy that online fuses power recommendations from both xApp types. It leverages a network digital twin to predict the utility of candidate actions and dynamically selects the optimal action based on real-time utility feedback and exponential weighted moving average error monitoring. System-level 5G evaluations demonstrate a normalized utility regret as low as 0.017 ± 0.006. Under severe digital twin drift (10 dB), the utility regret drops significantly from 11.19 ± 3.58 to 0.55 ± 0.25, substantially outperforming baseline methods.

Abstract

Open Radio Access Network (O-RAN) allows independently developed xApps to control RAN functions through the Near-Real-Time RAN Intelligent Controller (Near-RT RIC). When xApps with conflicting objectives operate concurrently, they may issue incompatible actions that degrade network performance. This paper addresses a direct conflict in which an energy-saving (ES) xApp and a coverage/throughput-oriented (CTO) xApp request different downlink transmit-power settings for the same cell. We formulate conflict resolution as online selection of a continuous blend of the two proposals, maximizing an energy-aware utility that jointly considers throughput and power consumption. A network digital twin (NDT) predicts this utility for candidate actions before live deployment, but selecting the highest twin-predicted utility becomes ineffective when the twin drifts. We therefore propose a twin-fidelity-aware hard-switching arbiter that monitors the error between predicted and observed utilities using an exponentially weighted moving average. While the error remains below a threshold, the arbiter follows the NDT-selected action; otherwise, it switches to the best previously observed action learned online. The arbiter is lightweight, training-free, and requires no oracle knowledge of the optimal policy. System-level 5G evaluations show that it achieves the closest throughput-power trade-off to the optimum across operator energy priorities, yielding normalized utility regret of $0.017 \pm 0.006$, versus $0.159 \pm 0.052$ for a COMIX-style twin-based selector. Under severe NDT drift (10 dB), it reduces utility regret from $11.19 \pm 3.58$ to $0.55 \pm 0.25$. These results show that online twin-fidelity monitoring enables robust digital-twin-assisted xApp conflict resolution while preserving utility-aware throughput-power optimization.

Problem

• xApp conflict
• Open RAN
• transmit power control
• energy-throughput trade-off
• digital twin

Innovation

• twin-fidelity-aware
• xApp conflict resolution
• network digital twin
• hard-switching arbiter
• energy-throughput trade-off