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Vehicular Network Spectrum Allocation using Hybrid NOMA and Multi-agent Reinforcement learning

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Main Authors: Alatabani, Lina Elmoiz, Saeed, Rashid A., Ali, Elmustafa Sayed, Mokhtar, Rania A., Khalifa, Othman Omran, Hayder, Gasim
Format: Proceeding Paper
Language:English
English
English
Published: Springer Nature Switzerland AG 2023 2023
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:http://irep.iium.edu.my/104626/2/104626_Vehicular%20Network%20Spectrum%20Allocation.pdf
http://irep.iium.edu.my/104626/1/Vehicular%20Network%20Spectrum%20Allocation.pdf
http://irep.iium.edu.my/104626/13/104626_Vehicular%20Network%20Spectrum%20Allocation%20Using%20Hybrid%20NOMA%20and%20Multi-agent%20Reinforcement%20Learning_SCOPUS.pdf
http://irep.iium.edu.my/104626/
http://doi.org/10.1007/978-3-031-26580-8_23
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spelling my.iium.irep.1046262024-02-03T01:46:07Z http://irep.iium.edu.my/104626/ Vehicular Network Spectrum Allocation using Hybrid NOMA and Multi-agent Reinforcement learning Alatabani, Lina Elmoiz Saeed, Rashid A. Ali, Elmustafa Sayed Mokhtar, Rania A. Khalifa, Othman Omran Hayder, Gasim TA Engineering (General). Civil engineering (General) Springer Nature Switzerland AG 2023 2023 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/104626/2/104626_Vehicular%20Network%20Spectrum%20Allocation.pdf application/pdf en http://irep.iium.edu.my/104626/1/Vehicular%20Network%20Spectrum%20Allocation.pdf application/pdf en http://irep.iium.edu.my/104626/13/104626_Vehicular%20Network%20Spectrum%20Allocation%20Using%20Hybrid%20NOMA%20and%20Multi-agent%20Reinforcement%20Learning_SCOPUS.pdf Alatabani, Lina Elmoiz and Saeed, Rashid A. and Ali, Elmustafa Sayed and Mokhtar, Rania A. and Khalifa, Othman Omran and Hayder, Gasim (2023) Vehicular Network Spectrum Allocation using Hybrid NOMA and Multi-agent Reinforcement learning. In: International Conference on Science Engineering Technology and Sustainability, SETS 2021, Virtual conference. http://doi.org/10.1007/978-3-031-26580-8_23 doi:10.1007/978-3-031-26580-8_23
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Alatabani, Lina Elmoiz
Saeed, Rashid A.
Ali, Elmustafa Sayed
Mokhtar, Rania A.
Khalifa, Othman Omran
Hayder, Gasim
Vehicular Network Spectrum Allocation using Hybrid NOMA and Multi-agent Reinforcement learning
format Proceeding Paper
author Alatabani, Lina Elmoiz
Saeed, Rashid A.
Ali, Elmustafa Sayed
Mokhtar, Rania A.
Khalifa, Othman Omran
Hayder, Gasim
author_facet Alatabani, Lina Elmoiz
Saeed, Rashid A.
Ali, Elmustafa Sayed
Mokhtar, Rania A.
Khalifa, Othman Omran
Hayder, Gasim
author_sort Alatabani, Lina Elmoiz
title Vehicular Network Spectrum Allocation using Hybrid NOMA and Multi-agent Reinforcement learning
title_short Vehicular Network Spectrum Allocation using Hybrid NOMA and Multi-agent Reinforcement learning
title_full Vehicular Network Spectrum Allocation using Hybrid NOMA and Multi-agent Reinforcement learning
title_fullStr Vehicular Network Spectrum Allocation using Hybrid NOMA and Multi-agent Reinforcement learning
title_full_unstemmed Vehicular Network Spectrum Allocation using Hybrid NOMA and Multi-agent Reinforcement learning
title_sort vehicular network spectrum allocation using hybrid noma and multi-agent reinforcement learning
publisher Springer Nature Switzerland AG 2023
publishDate 2023
url http://irep.iium.edu.my/104626/2/104626_Vehicular%20Network%20Spectrum%20Allocation.pdf
http://irep.iium.edu.my/104626/1/Vehicular%20Network%20Spectrum%20Allocation.pdf
http://irep.iium.edu.my/104626/13/104626_Vehicular%20Network%20Spectrum%20Allocation%20Using%20Hybrid%20NOMA%20and%20Multi-agent%20Reinforcement%20Learning_SCOPUS.pdf
http://irep.iium.edu.my/104626/
http://doi.org/10.1007/978-3-031-26580-8_23
_version_ 1792146370066382848
score 13.212058

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