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CommIT

Publications· 2023

Overview of the Urban Wireless Localization Competition

Çağkan Yapar, Fabian Jaensch, Ron Levie, Gitta Kutyniok, Giuseppe Caire

33rd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2023, Rome, Italy, September 17-20, 2023

Abstract

In dense urban environments, Global Navigation Satellite Systems do not provide good accuracy due to the low probability of line-of-sight (LOS) between the user equipment (UE) to be located and the satellites due to the presence of obstacles such as buildings. As a result, it is necessary to resort to other technologies that can operate reliably under non-line-of-sight (NLOS) conditions. To promote research in the reviving field of radio map-based wireless localization, we have launched the MLSP 2023 Urban Wireless Localization Competition. In this short overview paper, we describe the urban wireless localization problem, the provided datasets and baseline methods, the challenge task, and the challenge evaluation methodology. Finally, we present the results of the challenge.