5G High Density Demand Dataset in Liverpool City Region, UK

Area of Science:

• Telecommunications Engineering
• Data Science
• Network Performance Analysis

Background:

• Wireless network data offers insights into user behavior but is often inaccessible.
• Real-time data acquisition from service providers presents significant challenges.
• The need for realistic, publicly available datasets for 5G network research is critical.

Purpose of the Study:

• To present a comprehensive 5G dense deployment dataset for research and development.
• To address the scarcity of publicly available, high-fidelity wireless network data.
• To facilitate the analysis, prediction, and optimization of user behavior and network performance.

Main Methods:

• Utilized digital twin technology to generate a realistic 5G network dataset.
• Employed a system-level simulator for data modeling and analysis.
• Collected data from two high-density event venues: Salt & Tar and ACC Arena in Liverpool.

Main Results:

• Generated a dataset featuring 15,000 users across two venues.
• Included key performance indicators such as user position, traffic type, RU association, SINR, PRB, throughput, and BLER.
• Dataset validated through experimental measurements and released in an accessible format.

Conclusions:

• The presented 5G dataset is a valuable resource for understanding user behavior in dense environments.
• The methodology combining digital twins and system-level simulation provides a viable approach for dataset generation.
• The open release of this dataset will foster further research in 5G network optimization and performance analysis.