Zobrazeno 1 - 10
of 173
pro vyhledávání: '"Zeydan, Engin"'
Recently, large language models (LLMs) have been gaining a lot of interest due to their adaptability and extensibility in emerging applications, including communication networks. It is anticipated that 6G mobile edge computing networks will be able t
Externí odkaz:
http://arxiv.org/abs/2408.00722
Autor:
Zeydan, Engin, Vaca-Rubio, Cristian J., Blanco, Luis, Pereira, Roberto, Caus, Marius, Aydeger, Abdullah
In this paper, we present an innovative federated learning (FL) approach that utilizes Kolmogorov-Arnold Networks (KANs) for classification tasks. By utilizing the adaptive activation capabilities of KANs in a federated framework, we aim to improve c
Externí odkaz:
http://arxiv.org/abs/2407.20100
The transition to sustainable Open Radio Access Network (O-RAN) architectures brings new challenges for resource management, especially in predicting the utilization of Physical Resource Block (PRB)s. In this paper, we propose a novel approach to cha
Externí odkaz:
http://arxiv.org/abs/2407.14400
The need for intelligent and efficient resource provisioning for the productive management of resources in real-world scenarios is growing with the evolution of telecommunications towards the 6G era. Technologies such as Open Radio Access Network (O-
Externí odkaz:
http://arxiv.org/abs/2407.14377
Unlike other single-point Artificial Intelligence (AI)-based prediction techniques, such as Long-Short Term Memory (LSTM), probabilistic forecasting techniques (e.g., DeepAR and Transformer) provide a range of possible outcomes and associated probabi
Externí odkaz:
http://arxiv.org/abs/2407.14375
Autor:
Karaman, Bilal, Basturk, Ilhan, Taskin, Sezai, Kara, Ferdi, Zeydan, Engin, Yanikomeroglu, Halim
Natural disasters can have catastrophic consequences, a poignant example is the series of $7.7$ and $7.6$ magnitude earthquakes that devastated T\"urkiye on February 6, 2023. To limit the damage, it is essential to maintain the communications infrast
Externí odkaz:
http://arxiv.org/abs/2405.17635
The proliferation of mobile networks and their increasing importance to modern life, combined with the emerging threat of quantum computing, present new challenges and opportunities for cybersecurity. This paper addresses the complexity of protecting
Externí odkaz:
http://arxiv.org/abs/2404.10602
Autor:
Rezazadeh, Farhad, Barrachina-MuNoz, Sergio, Zeydan, Engin, Song, Houbing, Subbalakshmi, K. P., Mangues-Bafalluy, Josep
The rapid development of artificial intelligence (AI) techniques has triggered a revolution in beyond fifth-generation (B5G) and upcoming sixth-generation (6G) mobile networks. Despite these advances, efficient resource allocation in dynamic and comp
Externí odkaz:
http://arxiv.org/abs/2311.08798
Autor:
Rezazadeh, Farhad, Zanzi, Lanfranco, Devoti, Francesco, Barrachina-Munoz, Sergio, Zeydan, Engin, Costa-Pérez, Xavier, Mangues-Bafalluy, Josep
Artificial intelligence (AI) and Machine Learning (ML) are considered as key enablers for realizing the full potential of fifth-generation (5G) and beyond mobile networks, particularly in the context of resource management and orchestration. In this
Externí odkaz:
http://arxiv.org/abs/2307.02414
Along with the potential emergence of quantum computing, safety and security of new and complex communication services such as automated driving need to be redefined in the post-quantum era. To ensure reliable, continuous and secure operation of thes
Externí odkaz:
http://arxiv.org/abs/2112.06814