Name
Abstract | ||
|---|---|---|
Spectrum prediction is an important solution proposed to efficiently manage the scarce spectrum resource in various Dynamic Spectrum Access (DSA) applications. Deep Learning based models such as Long Short Term Memory (LSTM) have been increasingly applied to perform temporal and multi-dimensional prediction of future spectrum characteristics. These models have shown excellent capabilities to learn... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICSPCS53099.2021.9660229 | 2021 15th International Conference on Signal Processing and Communication Systems (ICSPCS) |
Keywords | DocType | ISBN |
Deep learning,Correlation,Communication systems,Dynamic spectrum access,Predictive models,Signal processing,Energy efficiency | Conference | 978-1-6654-3699-1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Niranjana Radhakrishnan | 1 | 0 | 1.01 |
| Sithamparanathan Kandeepan | 2 | 6 | 5.85 |
| Xinghuo Yu | 3 | 3 | 2.74 |
| Gianmarco Baldini | 4 | 1 | 1.38 |