Zobrazeno 1 - 10
of 365
pro vyhledávání: '"Yalin, E."'
Autor:
Sagduyu, Yalin E., Erpek, Tugba
LoRa provides long-range, energy-efficient communications in Internet of Things (IoT) applications that rely on Low-Power Wide-Area Network (LPWAN) capabilities. Despite these merits, concerns persist regarding the security of LoRa networks, especial
Externí odkaz:
http://arxiv.org/abs/2412.21164
In this paper, we address task-oriented (or goal-oriented) communications where an encoder at the transmitter learns compressed latent representations of data, which are then transmitted over a wireless channel. At the receiver, a decoder performs a
Externí odkaz:
http://arxiv.org/abs/2411.10385
Radio frequency (RF) communication has been an important part of civil and military communication for decades. With the increasing complexity of wireless environments and the growing number of devices sharing the spectrum, it has become critical to e
Externí odkaz:
http://arxiv.org/abs/2410.18283
Deep Reinforcement Learning (DRL) has been highly effective in learning from and adapting to RF environments and thus detecting and mitigating jamming effects to facilitate reliable wireless communications. However, traditional DRL methods are suscep
Externí odkaz:
http://arxiv.org/abs/2410.10521
Autor:
Demir, Utku, Davaslioglu, Kemal, Sagduyu, Yalin E., Erpek, Tugba, Anderson, Gustave, Kompella, Sastry
Integrated Sensing and Communication (ISAC) represents a transformative approach within 5G and beyond, aiming to merge wireless communication and sensing functionalities into a unified network infrastructure. This integration offers enhanced spectrum
Externí odkaz:
http://arxiv.org/abs/2410.08999
Autor:
Costa, Maice, Sagduyu, Yalin E.
Publikováno v:
Proc. 2024 IEEE International Conference on Communications Workshops, pp.554-559. %\thanks{Peer-reviewed version in Proc. 2024 IEEE International Conference on Communications Workshops (ICC Workshops), Denver, CO, USA, 2024, pp. 554-559
We consider the transfer of time-sensitive information in next-generation (NextG) communication systems in the presence of a deep learning based eavesdropper capable of jamming detected transmissions, subject to an average power budget. A decoy-based
Externí odkaz:
http://arxiv.org/abs/2410.08045
Autor:
Costa, Maice, Sagduyu, Yalin E.
Publikováno v:
In proceedings on IEEE VTC-Fall 2024 Conference
We consider the communication of time-sensitive information in NextG spectrum sharing where a deep learning-based classifier is used to identify transmission attempts. While the transmitter seeks for opportunities to use the spectrum without causing
Externí odkaz:
http://arxiv.org/abs/2410.05501
This paper explores opportunities and challenges of task (goal)-oriented and semantic communications for next-generation (NextG) communication networks through the integration of multi-task learning. This approach employs deep neural networks represe
Externí odkaz:
http://arxiv.org/abs/2401.01531
This paper studies the poisoning attack and defense interactions in a federated learning (FL) system, specifically in the context of wireless signal classification using deep learning for next-generation (NextG) communications. FL collectively trains
Externí odkaz:
http://arxiv.org/abs/2312.17164
Autor:
Sagduyu, Yalin E., Erpek, Tugba
Low-Power Wide-Area Network (LPWAN) technologies, such as LoRa, have gained significant attention for their ability to enable long-range, low-power communication for Internet of Things (IoT) applications. However, the security of LoRa networks remain
Externí odkaz:
http://arxiv.org/abs/2312.16715