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http://dx.doi.org/10.6109/jkiice.2022.26.5.703

Method of Predicting Path Loss and Base Station Topography Classification using Artificial Intelligent in Mobile Communication Systems  

Kim, Jaejeong (Innowireless Co., Ltd.)
Lee, Heejun (Innowireless Co., Ltd.)
Ji, Seunghwan (Innowireless Co., Ltd.)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.26, no.5, 2022 , pp. 703-713 More about this Journal
Abstract
Accurate and rapid establishment of mobile communication is important in mobile communication system. Currently, the base station parameters to establish a network are determined by cell planning tool. However, it is necessary to perform new cell planning for each new installation of the base station, and there may be a problem that parameters are not suitable for the actual environment are set, such as obstacle information that is not applied in the cell planning tool. In this paper, we proposed methods for path loss prediction using DNN and topographical division using CNN in SON server. After topography classification, a SON server configures the base station parameters according to topography, and update parameters for each topography. The proposed methods can configure the base station parameters automatically that are considered topography information and environmental changes.
Keywords
Mobile Communication System; SON (Self-Organization Network); DNN (Deep Neural Network); CNN (Convolutional Neural Network); Path Loss;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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