Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications

Mehmet Ariman*, Lal Verda Cakir, Mehmet Ozdem, Berk Canberk

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

1 Atıf (Scopus)

Özet

Unmanned air vehicles are becoming widespread, driven by improved wireless technologies. However, the WiFi technology used for communication has a highly crowded and unevenly distributed channel occupancy in its spectrum. To overcome this, WiFi resources need to be utilized efficiently. Therefore, this paper proposes the Opportunistic Reinforcement Learning-based WiFi Access scheme, which exploits intermittent channel occupancy to solve the NP-hard channel assignment problem. As a result, the proposed model has improved the accurate channel selection on the UAVs by 9%, performing 91% accuracy, compared to the trivial channel scoring-based selection algorithms.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9798350302523
DOI'lar
Yayın durumuYayınlandı - 2023
Harici olarak yayınlandıEvet
Etkinlik2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023 - Istanbul, Turkey
Süre: 25 Tem 202327 Tem 2023

Yayın serisi

Adı2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023

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???event.eventtypes.event.conference???2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023
Ülke/BölgeTurkey
ŞehirIstanbul
Periyot25/07/2327/07/23

Bibliyografik not

Publisher Copyright:
© 2023 IEEE.

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