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Conference Paper Poster: A Diffusion Model for Predicting Spectrum Efficiency in 5G Networks
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Authors
Gyeongjune Hahm, Kyung-yul Cheon, Hyeyeon Kwon, Seungkeun Park
Issue Date
2025-06
Citation
International Conference on Mobile Systems, Applications, and Services (MobiSys) 2025, pp.593-594
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1145/3711875.3734550
Abstract
This study proposes a regression diffusion model for predicting spectrum efficiency (SE) in 5G networks, addressing limitations of traditional analytical models in dense urban environments. Using 5G user equipment (UE) measurement data collected in Seoul, we developed a model that leverages SINR (Signal-to-Interference-plus-Noise Ratio) and TBS (Transport Block Size) as input variables with classifier-free guidance and hybrid loss functions. Experimental results demonstrate improved performance with 26.37% MAPE compared to alternative methods. The model accurately captures SE distribution characteristics and temporal variations, contributing to enhanced simulation accuracy for 5G network management in dense urban areas.
KSP Keywords
5G networks, Alternative method, Analytical model, Data collected, Dense urban, Improved performance, Network Management, Se distribution, Simulation accuracy, Spectrum efficiency, Temporal variation