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

Ariman, Mehmet; Cakir, Lal Verda; Özdem, Mehmet; Canberk, Berk

Abstract

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.

Citation

Ariman, M., Cakir, L. V., Özdem, M., & Canberk, B. (2023, July). Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications. Presented at 2023 International Conference on Smart Applications, Communications and Networking (SmartNets), Istanbul, Turkiye

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2023 International Conference on Smart Applications, Communications and Networking (SmartNets)
• Start Date: Jul 25, 2023
• End Date: Jul 27, 2023
• Acceptance Date: May 28, 2023
• Online Publication Date: Aug 22, 2024
• Publication Date: 2023
• Deposit Date: Oct 10, 2024
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Pages: 1-5
• Book Title: 2023 International Conference on Smart Applications, Communications and Networking (SmartNets)
• ISBN: 9798350302530
• DOI: https://doi.org/10.1109/smartnets58706.2023.10215658
• Keywords: Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications