Name
Abstract | ||
|---|---|---|
In this paper, an initial attempt to exploit the benefits of machine learning in solving relay selection for dualhop networks has been made. From data-driven perspective, we convert relay selection to multiclass-classification problem and propose a decision-tree-based selection scheme. Input features are generated by binary quantization to the equivalent channel state information of each relay, so... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TVT.2019.2909302 | IEEE Transactions on Vehicular Technology |
Keywords | Field | DocType |
Relays,Decision trees,Training data,Indexes,Machine learning,Feature extraction,Optimization | Decision tree,Mathematical optimization,Wireless,Computer science,Feature extraction,Electronic engineering,Quantization (signal processing),Maximization,Relay,Channel state information,Computational complexity theory | Journal |
Volume | Issue | ISSN |
68 | 6 | 0018-9545 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiao-Wei Wang | 1 | 596 | 59.78 |