Name
Abstract | ||
|---|---|---|
Automatic modulation classification (AMC) for overlapped sources plays an important role in spectrum monitoring and signal interception. In this paper, we propose a feature-based AMC framework for multiple overlapped sources. The framework first separates the overlapped sources via blind channel estimation and then conducts novel maximum-likelihood-based multicumulant classification (MLMC) for eac... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TVT.2016.2636324 | IEEE Transactions on Vehicular Technology |
Keywords | Field | DocType |
Modulation,Channel estimation,Monitoring,Maximum likelihood estimation,Wireless communication,Receiving antennas,Blind equalizers | Natural gradient,Wireless,Pattern recognition,Computer science,Maximum likelihood,Communication channel,Modulation,Cumulant,Independent component analysis,Artificial intelligence,Ratio test | Journal |
Volume | Issue | ISSN |
66 | 7 | 0018-9545 |
Citations | PageRank | References |
12 | 0.64 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sai Huang | 1 | 74 | 15.18 |
| Yuanyuan Yao | 2 | 19 | 3.11 |
| Zhiqing Wei | 3 | 107 | 28.35 |
| Zhiyong Feng | 4 | 794 | 167.21 |
| zhang | 5 | 210 | 25.85 |