Name
Title | ||
|---|---|---|
Path Planning for the Dynamic UAV-Aided Wireless Systems Using Monte Carlo Tree Search |
Abstract | ||
|---|---|---|
For UAV-aided wireless systems, online path planning attracts much attention recently. To better adapt to the real-time dynamic environment, for the first time, we propose a Monte Carlo Tree Search (MCTS)-based path planning scheme. In details, we consider a single UAV acts as a mobile server to provide computation tasks offloading services for a set of mobile users on the ground, where the movement of ground users follows a Random Way Point model. Our model aims at maximizing the average throughput under energy consumption and user fairness constraints, and the proposed time-saving MCTS algorithm can further improve the performance. Simulation results show that the proposed algorithm achieves a larger average throughput and a faster convergence performance compared with the baseline algorithms of Q-learning and Deep Q-Network. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TVT.2022.3160746 | IEEE Transactions on Vehicular Technology |
Keywords | DocType | Volume |
Unmanned aerial vehicle,path planning,Monte Carlo tree search,throughput maximization,computation task offloading | Journal | 71 |
Issue | ISSN | Citations |
6 | 0018-9545 | 0 |
PageRank | References | Authors |
0.34 | 14 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuwen Qian | 1 | 2 | 2.40 |
| Kexin Sheng | 2 | 0 | 0.34 |
| Chuan Ma | 3 | 0 | 1.01 |
| Jun Li | 4 | 747 | 90.31 |
| Ming Ding | 5 | 790 | 81.23 |
| MAHBUB HASSAN | 6 | 856 | 90.96 |