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pro vyhledávání: '"Jaensch, Fabian"'
In recent years, several studies have explored deep learning algorithms to predict large-scale signal fading, or path loss, in urban communication networks. The goal is to replace costly measurement campaigns, inaccurate statistical models, or comput
Externí odkaz:
http://arxiv.org/abs/2410.17264
Over the last years, several works have explored the application of deep learning algorithms to determine the large-scale signal fading (also referred to as ``path loss'') between transmitter and receiver pairs in urban communication networks. The ce
Externí odkaz:
http://arxiv.org/abs/2402.00878
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 Prediction Challenge. In this short overview paper, we briefly describe the pa
Externí odkaz:
http://arxiv.org/abs/2310.07658
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 likelihood of line-of-sight (LOS) links between the receiver (Rx) to be locat
Externí odkaz:
http://arxiv.org/abs/2212.00728
Autor:
Jaensch, Fabian, Jung, Peter
We consider a structured estimation problem where an observed matrix is assumed to be generated as an $s$-sparse linear combination of $N$ given $n\times n$ positive-semidefinite matrices. Recovering the unknown $N$-dimensional and $s$-sparse weights
Externí odkaz:
http://arxiv.org/abs/2003.12005
Autor:
Yapar, Cagkan, Jaensch, Fabian, Levie, Ron, Kutyniok, Gitta Astrid Hildegard, Caire, Giuseppe
Publikováno v:
Yapar, Jaensch, Levie, Kutyniok, Caire. Overview of the First Pathloss Radio Map Prediction Challenge. IEEE Open Jo
Externí odkaz:
https://hdl.handle.net/10037/35617
Autor:
Jaensch, Fabian1 (AUTHOR) f.jaensch@campus.tu-berlin.de, Jung, Peter2 (AUTHOR)
Publikováno v:
Information & Inference: A Journal of the IMA. Sep2022, Vol. 11 Issue 3, p1143-1171. 29p.
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