Zobrazeno 1 - 10
of 1 347
pro vyhledávání: '"A. Gaigalas"'
Autor:
Iturria-Rivera, Pedro Enrique, Gaigalas, Raimundas, Elsayed, Medhat, Bavand, Majid, Ozcan, Yigit, Erol-Kantarci, Melike
Extended Reality (XR) services are set to transform applications over 5th and 6th generation wireless networks, delivering immersive experiences. Concurrently, Artificial Intelligence (AI) advancements have expanded their role in wireless networks, h
Externí odkaz:
http://arxiv.org/abs/2411.14264
Autor:
Zhang, Han, Elsayed, Medhat, Bavand, Majid, Gaigalas, Raimundas, Ozcan, Yigit, Erol-Kantarci, Melike
Federated learning (FL) is an innovative distributed artificial intelligence (AI) technique. It has been used for interdisciplinary studies in different fields such as healthcare, marketing and finance. However the application of FL in wireless netwo
Externí odkaz:
http://arxiv.org/abs/2411.04159
Autor:
Si, Ran, Li, Yanting, Wang, Kai, Chen, Chongyang, Gaigalas, Gediminas, Godefroid, Michel, Jönsson, Per
The Graspg program package is an extension of Grasp2018 [Comput. Phys. Commun. 237 (2019) 184-187] based on configuration state function generators (CSFGs). The generators keep spin-angular integrations at a minimum and reduce substantially the execu
Externí odkaz:
http://arxiv.org/abs/2410.11297
Autor:
Salehi, Shavbo, Zhou, Hao, Elsayed, Medhat, Bavand, Majid, Gaigalas, Raimundas, Ozcan, Yigit, Erol-Kantarci, Melike
Network slicing is a pivotal paradigm in wireless networks enabling customized services to users and applications. Yet, intelligent jamming attacks threaten the performance of network slicing. In this paper, we focus on the security aspect of network
Externí odkaz:
http://arxiv.org/abs/2410.05153
Autor:
Habib, Md Arafat, Zhou, Hao, Iturria-Rivera, Pedro Enrique, Ozcan, Yigit, Elsayed, Medhat, Bavand, Majid, Gaigalas, Raimundas, Erol-Kantarci, Melike
Traffic Steering is a crucial technology for wireless networks, and multiple efforts have been put into developing efficient Machine Learning (ML)-enabled traffic steering schemes for Open Radio Access Networks (O-RAN). Given the swift emergence of n
Externí odkaz:
http://arxiv.org/abs/2409.20391
Autor:
Salehi, Shavbo, Iturria-Rivera, Pedro Enrique, Elsayed, Medhat, Bavand, Majid, Gaigalas, Raimundas, Ozcan, Yigit, Erol-Kantarci, Melike
In 5G networks, network slicing has emerged as a pivotal paradigm to address diverse user demands and service requirements. To meet the requirements, reinforcement learning (RL) algorithms have been utilized widely, but this method has the problem of
Externí odkaz:
http://arxiv.org/abs/2408.10376
Autor:
Habib, Md Arafat, Rivera, Pedro Enrique Iturria, Ozcan, Yigit, Elsayed, Medhat, Bavand, Majid, Gaigalas, Raimundus, Erol-Kantarci, Melike
Intent-based network automation is a promising tool to enable easier network management however certain challenges need to be effectively addressed. These are: 1) processing intents, i.e., identification of logic and necessary parameters to fulfill a
Externí odkaz:
http://arxiv.org/abs/2406.06059
Autor:
Iturria-Rivera, Pedro Enrique, Gaigalas, Raimundas, Elsayed, Medhat, Bavand, Majid, Ozcan, Yigit, Erol-Kantarci, Melike
Extended Reality (XR) services will revolutionize applications over 5th and 6th generation wireless networks by providing seamless virtual and augmented reality experiences. These applications impose significant challenges on network infrastructure,
Externí odkaz:
http://arxiv.org/abs/2405.15872
Doubly ionized cerium (Ce$^{2+}$) is one of the most important ions to understand the kilonova spectra. In particular, near-infrared (NIR) transitions of Ce III between the ground (5p$^6$ 4f$^2$) and first excited (5p$^6$ 4f 5d) configurations are re
Externí odkaz:
http://arxiv.org/abs/2405.05463
Autor:
Habib, Md Arafat, Iturria-Rivera, Pedro Enrique, Ozcan, Yigit, Elsayed, Medhat, Bavand, Majid, Gaigalas, Raimundus, Erol-Kantarci, Melike
This paper introduces an innovative method for predicting wireless network traffic in concise temporal intervals for Open Radio Access Networks (O-RAN) using a transformer architecture, which is the machine learning model behind generative AI tools.
Externí odkaz:
http://arxiv.org/abs/2403.10808