The transition to disaggregated and interoperable Open Radio Access Network (RAN) architectures and the introduction of RAN Intelligent Controllers (RICs) in O-RAN creates new resource optimization opportunities and fine-grained tuning and configuration of network components to save energy while fulfilling service demand. However, unlocking this potential requires fine-grained and accurate energy measurements across heterogeneous deployments. Three factors make this particularly challenging [...]. To address these challenges, we design the TENORAN framework, an automated measurement scaffold for fine-grained energy efficiency profiling of O-RAN deployments, and prototype it on a heterogeneous OpenShift cluster. TENORAN instruments an end-to-end deployment based on high-level specifications (e.g., gNB software stack and split options, traffic profiles), and collects synchronized performance metrics and power measurements for individual RAN components while the network is under controlled workloads including over-the-air traffic. Our experimental results demonstrate energy profiling of end-to-end experiments with xApps in the loop, energy efficiency differences between two RAN stacks, OpenAirInterface and srsRAN, in uplink and downlink, and core network power consumption trends.

翻译：向解耦且可互操作的开放无线接入网络架构的转型，以及在O-RAN中引入无线接入网络智能控制器，为网络组件的细粒度调优与配置创造了新的资源优化机会，从而在满足业务需求的同时实现节能。然而，释放这一潜力需要在异构部署环境中进行细粒度且精确的能耗测量。三大因素使得这一任务尤为困难[...]。为应对这些挑战，我们设计了TENORAN框架——一个用于对O-RAN部署进行细粒度能效剖析的自动化测量支架，并在异构OpenShift集群上实现了原型系统。TENORAN基于高层规范（例如gNB软件栈与切分选项、流量模型）对端到端部署进行插装，并在网络承受受控工作负载（包括空口流量）时，同步采集各无线接入网组件的性能指标与功耗数据。我们的实验结果表明：该框架能够对包含闭环xApps的端到端实验进行能耗剖析，揭示OpenAirInterface与srsRAN两种无线接入网栈在上行与下行链路的能效差异，并呈现核心网功耗的变化趋势。