한국정보통신학회논문지 (Journal of the Korea Institute of Information and Communication Engineering)

  • 제26권5호
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  • Pages.703-713
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  • 2022
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  • 2234-4772(pISSN)
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  • 2288-4165(eISSN)
한국정보통신학회 (The Korea Institute of Information and Commucation Engineering)
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이동통신 시스템에서 인공지능을 이용한 경로 손실 예측 및 기지국 지형 구분 방법

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

  • 투고 : 2022.04.08
  • 심사 : 2022.04.23
  • 발행 : 2022.05.31
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⟨ 이전 논문 다음 논문 ⟩

초록

이동통신 시스템에서 정확하고 신속한 통신망 구축은 중요하다. 현재 무선통신 시스템을 구성하기 위해서는 셀 플래닝 장비를 통해 기지국의 파라미터를 설정한다. 하지만 기지국의 신규 설치마다 셀 플래닝을 새로 수행해야 하며, 셀 플래닝에 반영되지 않은 장애물 정보 등 실제 환경과 맞지 않는 파라미터가 설정되는 문제가 발생할 수 있다. 이 논문에서는 SON 서버에서 기지국의 위치와 단말의 측정 정보를 이용한 DNN 모델을 통해 경로 손실 예측을 수행하고, 지형을 구분하는 CNN 모델을 통해 예측된 경로 손실의 지형을 구분한다. 구분된 지형을 바탕으로 SON 서버에서 해당 지형에 맞는 지형별 기지국 파라미터를 자동으로 설정하고 지속해서 지형별 파라미터를 업데이트하여, 지형과 주변 환경 변화를 고려한 기지국 파라미터를 자동으로 설정할 수 있다.

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.

키워드

과제정보

This work was supported by grant No. UC190001D(AI based mobile communication network autonomous operation technology considering tactical situations) from DAPA (Defense Acquisition Program Administration) and DITC(Defense Industry Technology Center)

참고문헌

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