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Real-time Localization Using Radio Maps

Signal Processing 2020-06-11 v1 Information Theory Machine Learning math.IT Machine Learning

Abstract

This paper deals with the problem of localization in a cellular network in a dense urban scenario. Global Navigation Satellite System typically performs poorly in urban environments when there is no line-of-sight between the devices and the satellites, and thus alternative localization methods are often required. We present a simple yet effective method for localization based on pathloss. In our approach, the user to be localized reports the received signal strength from a set of base stations with known locations. For each base station we have a good approximation of the pathloss at each location in the map, provided by RadioUNet, an efficient deep learning-based simulator of pathloss functions in urban environment, akin to ray-tracing. Using the approximations of the pathloss functions of all base stations and the reported signal strengths, we are able to extract a very accurate approximation of the location of the user.

Keywords

Cite

@article{arxiv.2006.05397,
  title  = {Real-time Localization Using Radio Maps},
  author = {Çağkan Yapar and Ron Levie and Gitta Kutyniok and Giuseppe Caire},
  journal= {arXiv preprint arXiv:2006.05397},
  year   = {2020}
}
R2 v1 2026-06-23T16:11:09.552Z