Zobrazeno 1 - 10
of 569
pro vyhledávání: '"interference classification"'
Autor:
Gaikwad, Nishant S., Heublein, Lucas, Raichur, Nisha L., Feigl, Tobias, Mutschler, Christopher, Ott, Felix
Federated learning (FL) enables multiple devices to collaboratively train a global model while maintaining data on local servers. Each device trains the model on its local server and shares only the model updates (i.e., gradient weights) during the a
Externí odkaz:
http://arxiv.org/abs/2410.15681
The expanding use of Unmanned Aerial Vehicles (UAVs) in vital areas like traffic management, surveillance, and environmental monitoring highlights the need for robust communication and navigation systems. Particularly vulnerable are Global Navigation
Externí odkaz:
http://arxiv.org/abs/2408.13056
Autor:
Heublein, Lucas, Feigl, Tobias, Nowak, Thorsten, Rügamer, Alexander, Mutschler, Christopher, Ott, Felix
Jamming devices present a significant threat by disrupting signals from the global navigation satellite system (GNSS), compromising the robustness of accurate positioning. The detection of anomalies within frequency snapshots is crucial to counteract
Externí odkaz:
http://arxiv.org/abs/2409.15114
This study delves into the classification of interference signals to global navigation satellite systems (GNSS) stemming from mobile jammers such as unmanned aerial vehicles (UAVs) across diverse wireless communication zones, employing federated lear
Externí odkaz:
http://arxiv.org/abs/2406.16102
Autor:
Ott, Felix, Heublein, Lucas, Raichur, Nisha Lakshmana, Feigl, Tobias, Hansen, Jonathan, Rügamer, Alexander, Mutschler, Christopher
Publikováno v:
IEEE 2024 International Conference on Localization and GNSS (ICL-GNSS)
Jamming devices pose a significant threat by disrupting signals from the global navigation satellite system (GNSS), compromising the robustness of accurate positioning. Detecting anomalies in frequency snapshots is crucial to counteract these interfe
Externí odkaz:
http://arxiv.org/abs/2402.09466
Publikováno v:
In Physical Communication August 2023 59
The growing number of devices using the wireless spectrum makes it important to find ways to minimize interference and optimize the use of the spectrum. Deep learning models, such as convolutional neural networks (CNNs), have been widely utilized to
Externí odkaz:
http://arxiv.org/abs/2303.03326
Akademický článek
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Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2022, Iss 1, Pp 1-23 (2022)
Abstract It is known that interference classification plays an important role in protecting the authorized communication system and avoiding its performance degradation in the hostile environment. In this paper, the interference classification proble
Externí odkaz:
https://doaj.org/article/d9d3b49fe1044f9fbd17332ec2c3e1b1
It is known that, interference classification plays an important role in protecting the authorized communication system and avoiding its performance degradation in the hostile environment. In this paper, the interference classification problem for th
Externí odkaz:
http://arxiv.org/abs/2108.10056