ArticlePloS one2023
LEO satellite assisted UAV distribution using combinatorial bandit with fairness and budget constraints.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- An Adjustable Wireless Backhaul Link Selection Algorithm for LEO-UAV-Sensor-Based Internet of Remote Things Network.Sensors (Basel, Switzerland) · 2024Article
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, an integration between a low earth orbit satellite (LEO-Sat) and unmanned aerial vehicle (UAV) is proposed to assist users in post-disaster areas. In this scenario, multiple UAVs will be distributed to fully cover the victims and provide rescue services, while LEO-Sat provides backhaul links for UAVs to the ground base station (GBS). In this regard, we consider the problem of efficient UAVs distribution to maximize the total sum rate of the victims while assuring fairness in their coverage within the limited resources of UAVs batteries and LEO-Sat bandwidth. In this paper, UAV distribution problem is considered as a combinatorial multi-armed bandit (MAB) with arms' fairness and limited UAVs battery budget (CMAB-FB) constraints. Additionally, the utilization of LEO-Sat bandwidth resources is optimized based on the average traffic demands of the LEO-UAV links by means of gradient decent algorithm. The results of numerical analysis indicate that the proposed approach outperforms other naïve ben chmarks.
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Registered trials
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