Optimization of UAV 3D trajectory in a post-disaster area using dual energy-aware bandits

Amrallah, Amr; Mohamed, Ehab Mahmoud; Tran, Gia Khanh; Sakaguchi, Kei

doi:10.1587/comex.2023tcl0015

Cited by 6 publications

(5 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A number of academic research papers have studied the benefits of MABS to provide universal coverage in DRN. These studies include [1][2][3][4][5][6][7][8][9][10].…”

Section: Mobile Aerial Base Stations For Coverage Services In Disastersmentioning

confidence: 99%

“…Work [3], underscores the critical importance of maximizing throughput in emergency scenarios to ensure efficient communication flow. Finally, the authors in [6] explore the application of UAVs for delivering wireless services during post-disaster periods, with a key objective of maximizing the coverage of ground users by optimizing the three-dimensional flight trajectories throughout the UAV flight missions.…”

Section: Mobile Aerial Base Stations For Coverage Services In Disastersmentioning

confidence: 99%

See 1 more Smart Citation

Optimizing Disaster Response through Efficient Path Planning of Mobile Aerial Base Station with Genetic Algorithm

Adam,

Nordin,

Abdullah

et al. 2024

Drones

View full text Add to dashboard Cite

The use of unmanned aerial vehicles (UAVs), or drones, as mobile aerial base stations (MABSs) in Disaster Response Networks (DRNs) has gained significant interest in addressing coverage gaps of user equipment (UE) and establishing ubiquitous connectivity. In the event of natural disasters, the traditional base station is often destroyed, leading to significant challenges for UEs in establishing communication with emergency services. This study explores the deployment of MABS to provide network service to terrestrial users in a geographical area after a disaster. The UEs are organized into clusters at safe locations or evacuation shelters as part of the communication infrastructure. The main goal is to provide regular wireless communication for geographically dispersed users using Long-Term Evolution (LTE) technology. The MABS traveling at an average speed of 50 km/h visits different cluster centroids determined by the Affinity Propagation Clustering (APC) algorithm. A combination of graph theory and a Genetic Algorithm (GA) was used through mutators with a fitness function to obtain the most efficient flyable paths through an evolution pool of 100 generations. The efficiency of the proposed algorithm was compared with the benchmark fitness function and analyzed using the number of serviced UE performance indicators. System-level simulations were used to evaluate the performance of the proposed new fitness function in terms of the UEs served by the MABS after the MABS deployment, fitness score, service ratio, and path smoothness ratio. The results show that the proposed fitness function improved the overall service of UEs after MABS deployment and the fitness score, service ratio, and path smoothness ratio under a given number of MABS.

show abstract

“…A number of academic research papers have studied the benefits of MABS to provide universal coverage in DRN. These studies include [1][2][3][4][5][6][7][8][9][10].…”

Section: Mobile Aerial Base Stations For Coverage Services In Disastersmentioning

confidence: 99%

Section: Mobile Aerial Base Stations For Coverage Services In Disastersmentioning

confidence: 99%

Optimizing Disaster Response through Efficient Path Planning of Mobile Aerial Base Station with Genetic Algorithm

Adam,

Nordin,

Abdullah

et al. 2024

Drones

View full text Add to dashboard Cite

show abstract

“…In [ 17 ], enhanced dynamic spectrum access was proposed empowered by MAB schemes for UAV networks in post-disaster scenario. This work was then extended in [ 18 ] to optimize the UAV 3D trajectory as well. Almost all work existing in literature regarding UAVs applications in post-disaster scenarios assumed that UAVs fly go-and-forth between the post-disaster zones and the ground fusion center in the nearest survival GBS.…”

Section: Literature Reviewmentioning

confidence: 99%

LEO satellite assisted UAV distribution using combinatorial bandit with fairness and budget constraints

Mohamed

2023

PLoS ONE

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…They can have advanced sensors and imaging technologies, enabling high-precision data collection, mapping, and analysis [4]. Moreover, they are increasingly recognized for their cost-effectiveness, accessibility, efficiency, precision, environmental benefits, and potential for use in various industries [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Joint User Association and Power Control in UAV Network: A Graph Theoretic Approach

Alnakhli,

Mohamed,

Abdulkawi

et al. 2024

Electronics

Self Cite

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs) have recently been widely employed as effective wireless platforms for aiding users in various situations, particularly in hard-to-reach scenarios like post-disaster relief efforts. This study employs multiple UAVs to cover users in overlapping locations, necessitating the optimization of UAV-user association to maximize the spectral and energy efficiency of the UAV network. Hence, a connected bipartite graph is formed between UAVs and users using graph theory to accomplish this goal. Then, a maximum weighted matching-based maximum flow (MwMaxFlow) optimization approach is proposed to achieve the maximum data rate given users’ demands and the UAVs’ maximum capacities. Additionally, power control is applied using the M-matrix theory to optimize users’ transmit powers and improve their energy efficiency. The proposed strategy is evaluated and compared with other benchmark schemes through numerical simulations. The simulation outcomes indicate that the proposed approach balances spectral efficiency and energy consumption, rendering it suitable for various UAV wireless applications, including emergency response, surveillance, and post-disaster management.

show abstract

Optimization of UAV 3D trajectory in a post-disaster area using dual energy-aware bandits

Cited by 6 publications

References 2 publications

Optimizing Disaster Response through Efficient Path Planning of Mobile Aerial Base Station with Genetic Algorithm

Optimizing Disaster Response through Efficient Path Planning of Mobile Aerial Base Station with Genetic Algorithm

LEO satellite assisted UAV distribution using combinatorial bandit with fairness and budget constraints

Joint User Association and Power Control in UAV Network: A Graph Theoretic Approach

Contact Info

Product

Resources

About