Name
Abstract | ||
|---|---|---|
Unmanned aerial vehicles (UAVs) are now widely used as backup base stations for the areas which lack of wire-less/cellular access. Since UAV does not depend on fundamental infrastructure, it plays an important role in emergency response and search & rescue. In the prior studies of the UAV-aided wireless coverage extension problem, it typically considers an outdoor scenario with Air-to-Ground path loss model. In this paper, we specify the problem with the use case of UAV-aided emergency rescue. In the new problem formulation, both indoor and outdoor path loss models are considered and the goal is to find an efficient deployment of minimum number of UAVs that guarantees the connection requirements. To solve this problem, we propose a heuristic approach which contains genetic based algorithm to arrange UAVs. During evaluation, our approach is compared with the brute-force search on randomly simulated emergencies. The results show that our approach could find efficient solution with much lower computation. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/SARNOF.2018.8720417 | 2018 IEEE 39th Sarnoff Symposium |
Keywords | Field | DocType |
UAV,wireless coverage,genetic algorithm | Software deployment,Wireless,Computer science,Computer network,Genetic algorithm,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-5386-6154-3 | 1 | 0.35 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guanxiong Liu | 1 | 4 | 1.08 |
| Hazim Shakhatreh | 2 | 22 | 2.91 |
| Abdallah Khreishah | 3 | 570 | 51.97 |
| Xiwang Guo | 4 | 34 | 2.67 |
| Nirwan Ansari | 5 | 4667 | 357.64 |