Measurement dataset and analysis code for "Measurement-Driven Modeling of End-to-End Latency in an Indoor Private Standalone 5G Network"

This record contains the measurement data and analysis code underlying the article "Measurement-Driven Modeling of End-to-End Latency in an Indoor Private Standalone 5G Network" (MDPI Network).

Context and methodology. End-to-end latency and throughput were measured in the private standalone 5G network of the TU Wien IFT TEC-Lab. Measurements were taken at seven fixed indoor locations, each situated directly beneath one of the seven pico radio units of the deployment. One-way latency was measured over UDP at six target traffic rates (1, 10, 50, 100, 200 and 500 Mbps) with five repetitions per condition, giving 210 runs; TCP throughput was measured with five repetitions per location, giving 35 runs. All measurements used iPerf 2.2.1 in enhanced-report mode, with 60-second runs and one-second reporting intervals. The latency campaign was carried out between 27 June and 3 July 2025 and the throughput campaign on 3 June, 27 June and 1 July 2025. Measurements characterise the complete path between a wired campus host and a 5G-attached endpoint, including campus routing and firewall functions, the private 5G core and radio access network, the customer premises equipment, and the wireless local-area link between the CPE and the receiving host.

Technical details. data.zip contains the processed per-trial datasets used in the article, including the achieved throughput parsed from the raw iPerf server reports. raw_latency_logs.zip and raw_throughput_logs.zip contain the unmodified iPerf output files. code.zip contains the MATLAB analysis pipeline in execution order, covering parsing, model fitting, bootstrap confidence-interval estimation, cross-validation, baseline comparison and the trial-level distribution analysis, together with an independent Python re-implementation used to verify the published parameter estimates. The MATLAB scripts were developed and run with MATLAB R2025b and require the Optimization Toolbox (lsqcurvefit); no other toolboxes are used. The Python scripts were tested with Python 3.14.6 under Windows 11, using both NumPy 2.4.6 and NumPy 2.5.2; the results agree between the two NumPy versions to at least six significant figures. NumPy is their only third-party dependency, and it is also declared in code/python/requirements.txt. All paths in the scripts are resolved relative to the script location, so the archives can be extracted anywhere.

Licensing. This record is dual-licensed. The CC BY 4.0 license applies to all data, that is to data.zip, raw_latency_logs.zip, raw_throughput_logs.zip and the README. All distributed code, that is the MATLAB and Python scripts in code.zip, is licensed under the MIT License. The full license texts are given in LICENSE.md, and the MIT license is additionally included inside code.zip as code/LICENSE-MIT.txt.

Further details. Three runs (location Q1, 50 Mbps, repetitions 3–5) returned invalid one-way delay values caused by a 32-bit counter wrap-around arising from residual clock offset between the two hosts. These runs are flagged by valid_owd = 0 in latency_trials_raw_210.csv and were replaced by the cell mean in latency_210.csv; script 10_imputation_sensitivity.m quantifies the effect. See Section 4.3.1 of the article. Models are fitted using the achieved throughput reported by iPerf, not the configured target rate.