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Conference Paper Intelligent Application for User Equipment Positioning in Open-RAN
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Authors
Sanghui Lee, Seung-Eun Hong, Hoon Lee, Jaewook Lee
Issue Date
2024-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2024, pp.2162-2164
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC62082.2024.10827713
Abstract
In this paper, we propose a novel artificial intelligence (AI) application in open radio access network (Open-RAN) framework to predict positions of user equipment (UE) in mobile networks. Specifically, we first analyze the characteristics of measured value (i.e., signal-to-noise ratio (SNR) value) at the mobile network, which will serve as the foundational input features for the AI application. Based on the analyzed results, we implement the moving average-based preprocessing technique in AI applications to eliminate randomness that could negatively impact prediction accuracy. Then, we design the AI model that utilizes the preprocessed data as input to predict UE positions. The evaluation results demonstrate that the proposed AI application predicts UE positions more accurately than an AI model without the preprocessing method.
KSP Keywords
AI Applications, Input features, Mobile networks, Moving average, Prediction accuracy, Preprocessing techniques, Radio Access Network(RAN), Signal noise ratio(SNR), Signal-to-Noise, artificial intelligence, impact prediction