Fifth-generation (5G) systems are increasingly studied as shared communication and computing infrastructure for connected vehicles, roadside edge platforms, and future unmanned-system applications. Yet results from simulators, host-OS emulators, digital twins, and hardware-in-the-loop testbeds are often compared as if timing, input/output (I/O), and control-loop behavior were equivalent across them. They are not. Consequently, apparent limits in throughput, latency, scalability, or real-time behavior may reflect the execution harness rather than the wireless design itself. This paper presents \textit{AtlasRAN}, a capability-oriented framework for modeling and performance evaluation of 5G Open Radio Access Network (O-RAN) platforms. It introduces two reference architectures, terminology that separates functional compatibility from timing fidelity, and a capability matrix that maps research questions to evaluation environments that can support them credibly. O-RAN is used here as an experimental coordinate system spanning Centralized Unit (CU)/Distributed Unit (DU) partitioning, fronthaul transport, control exposure, and core-network anchoring. We validate \textit{AtlasRAN} through a CU-DU uplink load study on a coherent CPU-GPU edge platform. For both a CPU-only baseline and a GPU-accelerated low-density parity-check decoding variant, aggregate goodput drops sharply as user count rises from 1 to 12, while fairness remains near ideal and compute utilization decreases rather than increases. This pattern indicates time-scale dilation and online I/O starvation in the emulation harness, not decoder saturation, as the dominant scaling limit. The key lesson is that timing, memory, and transport semantics must be reported as first-class experimental variables when evaluating ubiquitous 5G infrastructure.

翻译：第五代（5G）系统正日益被视为车联网、路侧边缘平台及未来无人系统应用的共享通信与计算基础设施进行研究。然而，来自模拟器、主机操作系统仿真器、数字孪生以及硬件在环测试平台的结果常被直接比较，仿佛它们在时序、输入/输出（I/O）及控制回路行为上是等效的。事实并非如此。因此，在吞吐量、时延、可扩展性或实时行为方面表现出的明显限制，可能反映的是执行框架而非无线设计本身的问题。本文提出\textit{AtlasRAN}，一种面向能力的5G开放式无线接入网（O-RAN）平台建模与性能评估框架。该框架引入两种参考架构、一套区分功能兼容性与时序保真度的术语体系，以及一个将研究问题映射至能够可靠支持这些问题的评估环境的能力矩阵。本文以O-RAN作为实验坐标系，涵盖集中单元（CU）/分布单元（DU）划分、前传传输、控制开放及核心网锚定等维度。我们通过在一致的CPU-GPU边缘平台上进行CU-DU上行链路负载研究来验证\textit{AtlasRAN}。无论是纯CPU基线方案还是GPU加速的低密度奇偶校验解码变体方案，当用户数从1增至12时，聚合有效吞吐量均急剧下降，而公平性保持接近理想状态，计算利用率不升反降。该模式表明仿真框架中的时间尺度膨胀与在线I/O资源匮乏是主导的可扩展性瓶颈，而非解码器饱和。关键启示在于：评估泛在5G基础设施时，必须将时序、内存及传输语义作为首要实验变量进行报告。