Name
Abstract | ||
|---|---|---|
In order to improve the detection probability of weak signals, a new eigenvalue-based detection scheme is used in cognitive radio system and attracts more attention. The limited distribution of the largest and the smallest eigenvalues is studied in the same framework based on Random Matrix Theory, and used to set the decision thresholds accordingly. A spectrum sensing scheme based on receiver nodes selection is proposed to significantly reduce the computational complexity with the expense of little detection performance loss. ©2010 IEEE. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/WCSP.2010.5633521 | WCSP |
Keywords | Field | DocType |
cognitive radio networks,eigenvalue,random matrix theory,spectrum sensing,covariance matrix,eigenvalues,signal to noise ratio,computational complexity,signal detection,cognitive radio network,sensors,cognitive radio | Mathematical optimization,Detection theory,Computer science,Matrix algebra,Signal-to-noise ratio,Algorithm,Real-time computing,Covariance matrix,Eigenvalues and eigenvectors,Computational complexity theory,Cognitive radio,Random matrix | Conference |
Volume | Issue | ISSN |
null | null | null |
Citations | PageRank | References |
2 | 0.44 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiwen Liu | 1 | 35 | 7.61 |
| hang zhang | 2 | 31 | 16.05 |
| shaofan sun | 3 | 5 | 0.82 |
| desheng zhu | 4 | 2 | 0.44 |