14 citations · 20 across the 7 of their papers we have counts for
5 papers · 1 filter
Radio Map Prediction from Noisy Environment Information and Sparse Observations
Fabian Jaensch, Çağkan Yapar, Giuseppe Caire +1
Many works have investigated radio map and path loss prediction in wireless networks using deep learning, in particular using convolutional neural networks. However, most assume pe…
The First Pathloss Radio Map Prediction Challenge
Çağkan Yapar, Fabian Jaensch, Ron Levie +2
To foster research and facilitate fair comparisons among recently proposed pathloss radio map prediction methods, we have launched the ICASSP 2023 First Pathloss Radio Map Predicti…
On the Effective Usage of Priors in RSS-based Localization
Çağkan Yapar, Fabian Jaensch, Ron Levie +1
In this paper, we study the localization problem in dense urban settings. In such environments, Global Navigation Satellite Systems fail to provide good accuracy due to low likelih…
Real-time Localization Using Radio Maps
Çağkan Yapar, Ron Levie, Gitta Kutyniok +1
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 environment…
RadioUNet: Fast Radio Map Estimation with Convolutional Neural Networks
Ron Levie, Çağkan Yapar, Gitta Kutyniok +1
In this paper we propose a highly efficient and very accurate deep learning method for estimating the propagation pathloss from a point (transmitter location) to any point …