H-RLS is proposed, a hierarchical multi-timescale framework that decouples control into a Non-RT Proximal Policy Optimization (PPO) agent for strategic, energy-aware policy planning and a Near-RT Recursive Least Squares (RLS)-assisted xApp that maintains zero SLA violations.
Abstract
The transition toward Open Radio Access Network (O-RAN) architecture has enabled unprecedented intelligence and flexibility in 5G and 6G network slicing. However, a fundamental challenge remains in managing the tension between radio unit energy efficiency and the strict Service Level Agreement (SLA) requirements of Ultra-Reliable Low-Latency Communication (URLLC) slices, particularly under highly dynamic traffic conditions. Existing O-RAN approaches suffer from a timescale conflict where Non-Real-Time (Non-RT) policy planners optimize for long-term energy but fail to react to rapid traffic surges, while Near-Real-Time (Near-RT) controllers prioritize reliability at the cost of significant energy over-provisioning. To address this, we propose H-RLS, a hierarchical multi-timescale framework that decouples control into a Non-RT Proximal Policy Optimization (PPO) agent for strategic, energy-aware policy planning and a Near-RT Recursive Least Squares (RLS)-assisted xApp. By predicting millisecond-level delay risks, the xApp acts as a mathematically constrained safety net, applying bounded tactical adjustments when critical SLA violations are detected. Extensive evaluations across dynamic traffic transitions demonstrate that H-RLS maintains zero SLA violations. By actively preventing resource over-provisioning, the framework achieves the lowest composite Energy-SLA cost across all tested regimes, significantly minimizing dynamic power consumption while preserving Enhanced Mobile Broadband (eMBB) service integrity.
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