| Detection technique | Performance metrics | ||
| Accuracy | Complexity | Robustness | |
| Energy detection | - at high SNRs, the performance is good - at low SNRs, the performance is unreliable - affected by noise uncertainty | - Low implementation complexity - convergence is reach by collecting higher number of samples | - orior information of PU signal isn’t required - inappropriate for spread spectrum signals - cannot differentiate a PU signal from other signal sources |
| Feature detection | - the performance is good at all SNRs | - medium complexity - convergence requires small number of samples | - require partial knowledge of PU signal - robust against noise uncertainty and interference - differentiate PU signal among different types of signal source |
| Matched filter and coherent detection | - best performance at all SNRs | - high complexity - convergence requires fewest number of samples | - require precise prior information PU signals |
| Covariance-based detection | - detection accuracy is high | - low computational complexity | - uncorrelated PU signals degrade detection Performance. - blind detection |