Name
Abstract | ||
|---|---|---|
In recent years, unmanned aircraft systems (UASs) have garnered significant attention, and the demand for communication utilizing unmanned aircrafts (UAs) has increased. However, the limited available frequency for UA communication, despite the increasing utilization, poses a problem. Moreover, for the practical application of UA communication, the changes and differences in the propagation environment and communication demand of each UA communication must be considered because of the variety of supposed services, and the considerable interference caused by obstacles and reflected waves, due to high UA mobility. In this research, we construct a UA communication management system at the UAS operating frequency, with reference to the physical channel configuration of the LTE and LTE Sidelink, utilizing Q-Learning. In addition, we determine the effectiveness of the proposed method by evaluating various propagation-environment scenarios and communication demands. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/tnse.2018.2842246 | IEEE Transactions on Network Science and Engineering |
Keywords | Field | DocType |
Long Term Evolution,Resource management,Device-to-device communication,Aircraft,Modulation,Interference | Resource management,Mathematical optimization,Operating frequency,Q-learning,Communication channel,Modulation,Resource allocation,Interference (wave propagation),Communications management,Mathematics,Distributed computing | Journal |
Volume | Issue | ISSN |
6 | 3 | 2327-4697 |
Citations | PageRank | References |
2 | 0.36 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuichi Kawamoto | 1 | 305 | 26.42 |
| Hiroaki Takagi | 2 | 2 | 0.36 |
| Hiroki Nishiyama | 3 | 1285 | 92.61 |
| Nei Kato | 4 | 3982 | 263.66 |