Energy-Latency Optimization for Dynamic Disaggregated Radio Access Networks

Abstract

In 5G networks, base station disaggregation and new services pose challenges for radio access network (RAN) configuration, particularly in meeting bandwidth and latency constraints. The BS disaggregation is enabled by functional splitting (FS), which distributes the RAN functions in processing nodes and alleviates latency and bandwidth requirements in the fronthaul (FH). In addition to network performance, energy consumption is a critical concern for mobile network operators (MNO), since RAN operations constitute a significant portion of their operational expenditure. RAN configuration optimization is essential for balancing service performance and cost-effective energy consumption. In this paper, we propose a mixed-integer linear programming (MILP) model incorporating three objective functions: (i) minimizing fronthaul latency, (ii) minimizing energy consumption, and (iii) a bi-objective optimization that jointly balances both latency and energy consumption. The model determines the optimal FS Option, RAN function placement, and routing for eMBB, URLLC, and mMTC slices. While prior studies have addressed RAN configuration from either an energy minimization or a latency reduction perspective, few have considered both aspects simultaneously in realistic scenarios. Our evaluation accounts for different topologies, accounts for variations in aggregated gNB demand, explores diverse FS combinations, and incorporates Time Sensitive Networking modeling for latency analysis, which is critical for RAN performance. Given that MILP execution can be computationally intensive, we propose a heuristic algorithm that adheres to RAN constraints while providing near-optimal solutions. The results reveal an inherent trade-off between latency and energy consumption, highlighting the need for dynamic RAN reconfiguration. These insights provide a foundation for optimizing existing and future RAN deployments.