Name
Abstract | ||
|---|---|---|
Recent advances in wireless technologies have led to several autonomous deployments of such networks. As nodes across distributed networks must co-exist, it is important that all transmitters and receivers are aware of their radio frequency (RF) surroundings so that they can adapt their transmission and reception parameters to best suit their needs. To this end, machine learning techniques have be... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TCCN.2019.2948919 | IEEE Transactions on Cognitive Communications and Networking |
Keywords | DocType | Volume |
Radio transmitters,Radio frequency,Gallium nitride,Data models,Generators,Artificial neural networks | Journal | 6 |
Issue | ISSN | Citations |
2 | 2332-7731 | 11 |
PageRank | References | Authors |
0.50 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| debashri roy | 1 | 18 | 3.42 |
| Tathagata Mukherjee | 2 | 14 | 4.97 |
| Mainak Chatterjee | 3 | 1562 | 175.84 |
| Erik Blasch | 4 | 1051 | 90.91 |
| Eduardo L. Pasiliao | 5 | 233 | 39.13 |