Name
Abstract | ||
|---|---|---|
Spectrum occupancy prediction allows cognitive radio secondary users to exploit temporal spectrum opportunities one step-ahead. Temporal correlations in spectrum sensing measurements can be utilized to predict primary user activity patterns. Where applicable, cooperative spectrum prediction has the potential to improve prediction accuracy compared to single user (local) spectrum prediction. This l... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LCOMM.2018.2861008 | IEEE Communications Letters |
Keywords | Field | DocType |
Hidden Markov models,Predictive models,Sensors,Probability,Signal to noise ratio,Markov processes,Erbium | Mean squared prediction error,Markov process,Computer science,Spectrum occupancy,Signal-to-noise ratio,Fusion,Algorithm,Real-time computing,Exploit,Hidden Markov model,Cognitive radio | Journal |
Volume | Issue | ISSN |
22 | 10 | 1089-7798 |
Citations | PageRank | References |
4 | 0.40 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hamid Eltom | 1 | 12 | 1.89 |
| Kandeepan Sithamparanathan | 2 | 513 | 47.90 |
| Liang Ying-Chang | 3 | 10007 | 593.03 |
| Robin J. Evans | 4 | 1333 | 168.58 |