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Real-time Localization Using Radio Maps (2006.05397v1)

Published 9 Jun 2020 in eess.SP, cs.IT, cs.LG, math.IT, and stat.ML

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.

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Authors (4)
  1. Çağkan Yapar (49 papers)
  2. Ron Levie (40 papers)
  3. Gitta Kutyniok (120 papers)
  4. Giuseppe Caire (358 papers)
Citations (3)

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