README file About the data set >> 5G High Density Demand (HDD) Dataset in Liverpool City Region, UK (Supplement) Dataset creators >> Mukesh Kumar Maheshwari1(ORCID: 0000-0002-2843-9758), Alessandro Raschella1 (ORCID: 0000-0002-1626-8947), Michael Mackay1 (ORCID: 0000-0001-9013-7884), Max Hashem Eiza1 (ORCID: 0000-0001-9114-8577), Jon Wetherall2 and Jen Laing2 1School of Computer Science and Mathematics, Liverpool John Moores University, Liverpool, L3 3AF, UK. 2 CGA Simulation, L8 1XE, UK. Organisations with which the creators are affiliated: >> Liverpool John Moores University, Liverpool, UK >> CGA Simulation, Liverpool, UK. Rights holder(s) for the dataset : Alessandro Raschella Description >> The wireless network data are a feasible way to understand the user behaviour in a given environment and may be utilized for analysis, prediction and optimization. On the other hand, datasets from wireless service providers are not publicly available, and obtaining a dataset in real time is challenging. In this work, we present a software/tool to generate a 5G dense deployment dataset obtained from the Liverpool City Region High Density Demand (LCR HDD) project. The project involves network deployment and assessment at Salt Tar and the ACC Arena event venues located in the city of Liverpool. Digital twin technology is considered to generate the realistic user positions, which is inputted to a system-level simulator for data modelling and analysis. The package consists of (i) a digital twin user interface developed by CGA, (ii) guidelines to configure the Vienna 5G system-level simulator, and (iii)a MATLAB script to extract the result. The package presented is utilized to collect a dataset that is publicly available at the LJMU repository (https://opendata.ljmu.ac.uk/id/eprint/236/). Data collection or generation methods, important characteristics, etc. >> Digital twin model developed by CGA Simulation and MATLAB based simulator How the dataset should be cited: Maheshwari, Mukesh Kumar, Raschella, Alessandro, Mackay, Michael, Eiza, Max Hashem, Wetherall, Jon and Laing, Jen (2025) 5G High Density Demand (HDD) Dataset in Liverpool City Region, UK (Supplement). [Data Collection] https://doi.org/10.24377/LJMU.d.00000251 Related data : https://doi.org/10.24377/LJMU.d.00000236 Contact details >> m.i.mackay@ljmu.ac.uk Terms of use Creative Commons licence : Deed - Attribution 4.0 International - Creative Commons  Please contact researchonline@ljmu.ac.uk to gain access to this dataset. Please provide the following details: 1. What is your full name and institutional affiliation? 2. What is your email address and contact information? 3. What is your role or position (e.g., student, researcher, faculty, industry professional)? 4. What is the purpose of your request to access this dataset? 5. How do you intend to use the data (e.g., for research, teaching, validation, etc.)? 6. Please provide a brief description of your project or research topic. 7. Will the data be used for commercial purposes? (Yes/No) 8. Will the data be shared with anyone else? If yes, please specify. 9. Do you agree to acknowledge the dataset and cite its DOI in any publications using it? (Yes/No) Project and funding information Title: Specify the title of the project >> Liverpool City Region High Density Demand (LCR HDD) project. Project starts and end dates >> September 2023–March 2025 Funding organisation name >> Department for Digital, Culture, Media and Sport, Innovate UK Contents >> Digital twin application (.exe) and supporting files. >> Guidelines in word file (.docx). >> MATLAB script (.m file). Methods >> The L5G simulator consists of two main components: a digital twin-based model of the venues and a MATLAB-based simulator of the deployments. The digital twin component is developed by CGA simulation, a virtual simulation capable of solving real-world problems based on realistic user behaviour in terms of mobility and data traffic, achieved from real events. The MATLAB-based component is built upon the Vienna 5G System Level (SL) Simulator, which has the capability to mimic buildings, streets, radio environment conditions, such as path loss and shadowing, developed according to real-world scenarios based on data available in the OpenStreetMap (OSM) database. The MATLAB-based component can gather information from the radio environments and compute key performance parameters based on the input generated by the digital twin-based component, including downlink (DL) and uplink (UL) SINR (dB), user throughput (Mbps), PRB utilization, and BLER at every timestamp for each user, considering their current position and application. >> M. K. Maheshwari, et al., “5G High Density Demand Dataset in Liverpool City Region, UK”, Sci Data. (Article in progress). 2025