Name
Title | ||
|---|---|---|
Distributive Dynamic Spectrum Access Through Deep Reinforcement Learning: A Reservoir Computing-Based Approach. |
Abstract | ||
|---|---|---|
Dynamic spectrum access (DSA) is regarded as an effective and efficient technology to share radio spectrum among different networks. As a secondary user (SU), a DSA device will face two critical problems: 1) avoiding causing harmful interference to primary users (PUs) and 2) conducting effective interference coordination with other SUs. These two problems become even more challenging for a distrib... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/JIOT.2018.2872441 | IEEE Internet of Things Journal |
Keywords | DocType | Volume |
Sensors,Machine learning,Recurrent neural networks,Dynamic spectrum access,Reservoirs,Interference,Training | Journal | 6 |
Issue | ISSN | Citations |
2 | 2327-4662 | 13 |
PageRank | References | Authors |
0.58 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hao-Hsuan Chang | 1 | 22 | 3.17 |
| Hao Song | 2 | 50 | 12.34 |
| Yang Yi | 3 | 159 | 26.70 |
| Jianzhong (Charlie) Zhang | 4 | 64 | 6.12 |
| Haibo He | 5 | 3653 | 213.96 |
| Lingjia Liu | 6 | 799 | 92.58 |