Detection Fusion by Hierarchy Rule for Cognitive Radio

Cooperation between cognitive radio nodes is indispensable in order to mitigate the sensitivity requirement on individual radio and increase the reliability of spectrum sensing. Normally the fusion network is in parallel configuration and the conventional fusion rules are the k out of N rules because of their simplicity to manage. When the detection nodes are similar with each other i.e. their observations are from same probability distribution, the k out of N rules can make improvement to detection performance since they are equivalent to Neyman-Pearson criteria in this case. However the detection performance decreases greatly when the detection nodes are dissimilar due to fading and shadowing of radio channels especially when most of them are at low SNR states. The hierarchy fusion scheme we proposed in this paper incorporates both parallel and serial configuration and classifies detection nodes into different groups by their SNR levels. The receiver operating characteristic (ROC) of hierarchy fusion rule shows that the detection efficiency and reliability can be increased no matter the detection nodes are similar or dissimilar.