標題: Improving the Localization Accuracy for Sigfox Low-Power Wide Area Networks
作者: Wang, Shie-Yuan
Cheng, Yu-Hsiang
Tarng, Jenn-Hwan
交大名義發表
資訊工程學系
National Chiao Tung University
Department of Computer Science
公開日期: 1-Jan-2019
摘要: Sigfox is a new LPWAN (Low-Power Wide Area Networks) wireless technology proposed for IoT applications. Its transmit power is only 22.5 dBm, but its wireless transmission range can be up to 30 km in open space. In this paper, we propose a new machine learning-based localization method to predict the location of a Sigfox module. Our method divides the space around each base station into a few sectors and trains a more accurate path-loss-to-distance model for each sector to reflect its site specific multipath propagation environment. Our experimental results measured in a big city show that the maximum distance errors of our method are much smaller than those of the official Sigfox localization service in many cases.
URI: http://hdl.handle.net/11536/155530
ISBN: 978-1-7281-2999-0
ISSN: 1530-1346
期刊: 2019 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC)
起始頁: 378
結束頁: 383
Appears in Collections:Conferences Paper