Proceedings of the Korean Society of Computer Information Conference (한국컴퓨터정보학회:학술대회논문집)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Optimize OTDOA-based Positioning Accuracy by Utilizing Multiple Linear Regression Model under NB-IoT Technology

NB-IoT 기술에서 Multiple Linear Regression Model을 활용하여 OTDOA 기반 포지셔닝 정확도 최적화

  • Pan, Yichen (School of Computer Science and Engineering, Kyungpook National University) ;
  • Kim, Jaesoo (School of Computer Science and Engineering, Kyungpook National University)
  • 판이첸 (경북대학교 IT대학 컴퓨터학부) ;
  • 김재수 (경북대학교 IT대학 컴퓨터학부)
  • Published : 2020.07.15
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Abstract

NB-IoT(Narrow Band Internet of Things) is an emerging LPWAN(Low Power Wide Area Network) radio technology. NB-IoT has many advantages like low power, low cost, and high coverage. However low bandwidth and low sampling rates also lead to poor positioning accuracy. This paper proposed a solution to optimize positioning accuracy under the OTDOA(Observed Time Difference of Arrival) approach by utilizing MLR(Multiple Linear Regression) models. Through the MLR model to predict the influence degree of weather(temperature, humidity, light intensity and air pressure) on the arrival time of signal transmission to improve the measurement accuracy. The improvement of measurement accuracy can greatly improve IoT applications based on NB-IoT.

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