Overview of the Urban Wireless Localization Competition

Yapar, Çağkan; Jaensch, Fabian; Levie, Ron; Kutyniok, Gitta und Caire, Giuseppe (2023): Overview of the Urban Wireless Localization Competition. 2023 IEEE: 33rd International Workshop on Machine Learning for Signal Processing (MLSP), Rome, Italy, 17. -20. September 2023. In: 2023 IEEE: 33rd International Workshop on Machine Learning for Signal Processing (MLSP), IEEE. pp. 1-6

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.

• Item Type: Conference or Workshop Item (Paper)
• Faculties: Mathematics, Computer Science and Statistics > Mathematics > Bavarian Chair for Mathematical Foundations of Artificial Intelligence
• Subjects: 500 Science > 510 Mathematics
• Language: English