Name
Abstract | ||
|---|---|---|
Driven by the unprecedented high throughput and low latency requirements anticipated for next generation wireless networks, this article introduces an artificial intelligence (AI)-enabled framework in which unmanned aerial vehicles use non-orthogonal multiple access and mobile edge computing techniques to serve terrestrial mobile users (MUs). The proposed framework enables terrestrial MUs to offlo... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MWC.121.2100058 | IEEE Wireless Communications |
Keywords | DocType | Volume |
NOMA,Wireless networks,Reinforcement learning,Throughput,Unmanned aerial vehicles,Resource management,Quality of experience | Journal | 28 |
Issue | ISSN | Citations |
5 | 1536-1284 | 1 |
PageRank | References | Authors |
0.35 | 13 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Zhong | 1 | 16 | 1.87 |
| Mingzhe Chen | 2 | 595 | 44.32 |
| Xiao Liu | 3 | 284 | 41.90 |
| Yuanwei Liu | 4 | 2162 | 131.65 |
| Yue Chen | 5 | 291 | 24.27 |
| Shuguang Cui | 6 | 521 | 54.46 |
| H. V. Poor | 7 | 25411 | 1951.66 |