Name
Abstract | ||
|---|---|---|
Radio frequency sources are observed at a fusion center via sensor measurements made over slow flat-fading channels. The number of sources may be larger than the number of sensors, but their activity is sparse and intermittent with bursty transmission patterns. To account for this, sources are modeled as hidden Markov models with known or unknown parameters. The problem of blind source estimation ... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TVT.2019.2933996 | IEEE Transactions on Vehicular Technology |
Keywords | Field | DocType |
Hidden Markov models,Estimation,Wireless networks,Dictionaries,Fading channels,Channel estimation,Source separation | Computer science,Expectation–maximization algorithm,Fading,Lasso (statistics),Filter (signal processing),Algorithm,Electronic engineering,Hidden Markov model,Blind signal separation,Source separation,Channel state information | Journal |
Volume | Issue | ISSN |
68 | 10 | 0018-9545 |
Citations | PageRank | References |
1 | 0.39 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Annan Dong | 1 | 1 | 0.39 |
| Osvaldo Simeone | 2 | 3574 | 264.99 |
| Alexander M. Haimovich | 3 | 618 | 69.28 |
| Jason A. Dabin | 4 | 27 | 4.57 |