The Journal of Korean Institute of Information Technology (한국정보기술학회논문지)

Korean Institute of Information Technology (한국정보기술학회)
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Study of Localization Based on Fingerprinting Technique Using Uplink CSI in Cloud Radio Access Network

클라우드 무선접속 네트워크에서 상향링크 채널 상태 정보를 이용한 핑거프린팅 기반 실내 측위에 관한 연구 시스템

  • 우상우 (한국교통대학교 정보기술융합학과) ;
  • 이상헌 (연세대학교 전기전자공학부) ;
  • 문철 (한국교통대학교 전자공학과)
  • Received : 2018.12.18
  • Accepted : 2019.01.25
  • Published : 2019.02.28
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Abstract

With 5G standards proceeding in earnest and increasing demand for services of indoor localization, research on indoor location recognition is being studied in various industrial fields, and research based on fingerprint recognition technology using Wireless Local Area Network (WLAN) is representative. In this paper, we propose an indoor positioning system based on fingerprinting technique that uses Cloud Radio Access Network (C-RAN) architecture and Channel State Information (CSI). In order to improve the performance in indoor positioning, we combined existing fingerprinting method and K nearest neighbor (KNN) technology which is one of the machine running technique. The performance improvements of the proposed indoor positioning system was verified by comparative experiments with the existing localization technique in a indoor localizztion testbed.

최근 5G 표준화가 본격화되고 실내위치관련 서비스에 대한 수요가 증가하면서, 실내 측위 기술에 대한 연구가 다양한 산업분야에서 연구되고 있으며, WLAN(Wireless Local Area Network)을 이용한 핑거프린팅 기법 기반의 연구가 대표적이다. 본 논문은 UDN(Ultra Dense Network) 환경에서 C-RAN(Cloud Radio Access Network) 구조와 상향링크 CSI(Channel State Information)를 측위 기반정보로 사용하는 실내 측위 기술을 제안한다. 기존의 핑거프린팅 방식에 머신러닝 기술 중 하나인 KNN(K Nearest Neighbor) 기술을 결합하여 측위 정확도를 개선하였으며, 성능 분석을 위해 구축된 테스트베드에서 수행된 기존 실내 측위 기술과 제안 기술의 성능 비교 실험을 통해, 제안하는 기술이 측위 정확도를 개선함을 확인하였다.

Keywords

References

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