Name
Title | ||
|---|---|---|
Deep Reinforcement Learning for Mobile 5G and Beyond: Fundamentals, Applications, and Challenges |
Abstract | ||
|---|---|---|
Future-generation wireless networks (5G and beyond) must accommodate surging growth in mobile data traffic and support an increasingly high density of mobile users involving a variety of services and applications. Meanwhile, the networks become increasingly dense, heterogeneous, decentralized, and ad hoc in nature, and they encompass numerous and diverse network entities. Consequently, different o... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/MVT.2019.2903655 | IEEE Vehicular Technology Magazine |
Keywords | DocType | Volume |
5G mobile communication,Optimization,Vehicle dynamics,Neural networks,Power control,Wireless networks | Journal | 14 |
Issue | ISSN | Citations |
2 | 1556-6072 | 21 |
PageRank | References | Authors |
0.57 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zehui Xiong | 1 | 586 | 54.94 |
| Yang Zhang | 2 | 313 | 19.51 |
| Niyato Dusit | 3 | 9486 | 547.06 |
| Ruilong Deng | 4 | 627 | 41.64 |
| Ping Wang | 5 | 4153 | 216.93 |
| Li-Chun Wang | 6 | 613 | 60.61 |