236 17 1676 3 4505 document 1676 Readme_5G High Density Demand (HDD) Dataset in Liverpool City Region UK.txt text/plain 86b94df5836449d4cf5aad6c9a8b3d31 MD5 4505 2025-06-25 14:45:24 https://opendata.ljmu.ac.uk/id/eprint/236/2/Readme_5G%20High%20Density%20Demand%20%28HDD%29%20Dataset%20in%20Liverpool%20City%20Region%20UK.txt 236 2 2 text/plain text en public cc_by_4

Readme_5G High Density Demand (HDD) Dataset in Liverpool City Region UK.txt

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indexcodes.txt

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L5GHDD_Dataset.zip

data Collection 1680 3 4515 document 1680 Readme_ MS Word with images.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document 7324fafc1576e418a689f4df0c89301d MD5 79371 2025-06-26 07:43:44 https://opendata.ljmu.ac.uk/id/eprint/236/5/Readme_%20MS%20Word%20with%20images.docx 236 5 5 application/vnd.openxmlformats-officedocument.wordprocessingml.document text en public cc_by_4

Readme_ MS Word with images.docx

readme Text 1681 1 4518 document 1681 indexcodes.txt text/plain 32c8caebfbf759166864713711b8b50b MD5 2019 2025-06-26 08:03:47 https://opendata.ljmu.ac.uk/id/eprint/236/6/indexcodes.txt 236 6 6 text/plain Generate index codes conversion from text to indexcodes en public

indexcodes.txt

http://eprints.org/relation/isVersionOf https://opendata.ljmu.ac.uk/id/document/1680 http://eprints.org/relation/isVolatileVersionOf https://opendata.ljmu.ac.uk/id/document/1680 http://eprints.org/relation/isIndexCodesVersionOf https://opendata.ljmu.ac.uk/id/document/1680 archive 7 disk0/00/00/02/36 2025-06-26 07:58:41 2025-10-29 10:54:38 2025-06-26 07:58:41 data_collection show 7 Maheshwari Mukesh Kumar 0000-0002-2843-9758 Alessandro Raschella 0000-0002-1626-8947 Michael Mackay Max Hashem Eiza Jon Wetherall Jen Laing CGA Simulation, L8 1XE, UK ict public 400608 Wireless communication systems and technologies (incl. microwave and millimetrewave) EMBARGO REQUESTED BY DEPOSITING USER: Embargo name: Unknown Depositing user's comment: According to the journal submission guidelines for the first round of review, data are available for download and review by reviewers via any URL that allows anonymous downloads. ----- Depositing user's licence comment: The wireless network data are a feasible way to understand the user behavior 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 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 dataset, which is inputted to a system level simulator for data modeling and analysis. The data set consists of 3,000 users in the Salt Tar venue and 12,000 users in the ACC Arena venue with features including users' position, traffic type, Radio Unit (RU) association, Signal to Interference and Noise Ratio (SINR), Physical Resource Blocks (PRB), throughput, Block Error Rate (BLER), and a total length of 10,000 samples. The dataset is validated through experimental measurements and is released in a simple format for easy access. 2025-06-20 published 10.24377/LJMU.d.00000236 Alessandro Raschella 400608 Digital twin model and Matlab based simulator English English 2025-03-03 2025-06-13 https://doi.org/10.24377/LJMU.d.00000251 dat 2025-06-20