Optimal cooperative spectrum sensing in cognitive radio networks

Spectrum sensing is a key enabling functionality in cognitive radio networks, which detects signal from licensed primary radios to avoid harmful interference. However, due to the effects of channel fading, individual cognitive radios may not be able to reliably detect the existence of a primary radio. In this paper, we proposed an optimal linear cooperation framework for spectrum sensing in order to accurately detect the weak primary signal. Based on Neyman-Pearson criterion, we obtain an optimal sensing scheme that maximizes the detection probability for a given false alarm probability.