AtlasRAN: Modeling and Performance Evaluation of Open 5G Platforms for Ubiquitous Wireless Networks

2026-03-15

AI Summary

Existing 5G simulation and testing platforms struggle to accurately assess real-world wireless system performance due to timing distortions, I/O bottlenecks, and discrepancies in control-loop behavior. This work proposes AtlasRAN, a novel framework that introduces a capability-oriented evaluation paradigm. By defining a reference architecture and a capability matrix, AtlasRAN explicitly distinguishes between functional compatibility and timing fidelity, and establishes a mapping mechanism between research questions and experimental setups. Leveraging the O-RAN coordinate system—which encompasses CU/DU split, fronthaul transport, and control-plane exposure—the study conducts uplink experiments on a CPU-GPU edge platform. Results reveal that throughput degradation stems from timing dilation and I/O starvation in simulation environments, not decoder saturation, thereby demonstrating that timing, memory, and transport semantics must be reported as critical experimental variables to significantly enhance the scientific rigor and credibility of 5G infrastructure evaluation.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Evaluation and Analysis
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Web data generation and simulation

Abstract

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.

Problem

• 5G
• O-RAN
• performance evaluation
• timing fidelity
• emulation

Innovation

• AtlasRAN
• O-RAN
• timing fidelity
• capability matrix
• CU-DU partitioning