Characterization of spatial diversity in cooperative spectrum sensing

Cognitive radios (CR) and dynamic spectrum access (DSA) provide an efficient way to exploit underutilized radio spectrum by allowing secondary users to access licensed frequencies in an agile manner. This principle allows secondary users to access a licensed frequency band when their transmission will not interfere the primary receiver. Consequently, spectrum sensing is needed by the secondary users to describe the state of a licensed frequency band as vacant or occupied, which can be for a single user a challenging task due to the random nature of the wireless channel. In order to mitigate the effects of channel fading on detection, cooperative detection algorithms have been proposed in the literature. The gain from cooperation comes from spatial diversity as the signal is observed via multiple independent channels. In order to characterize spatial diversity in multichannel signal detection we propose a measure for the spatial diversity. We define spatial diversity as the maximum slope of the probability of detection curve in the logarithmic SNR scale. This definition looks promising for three reasons: 1) it shows that diversity is obtained with diminishing returns as the number of sensors is increased, 2) the number of samples has very little effect and 3) it shows very little gain for correlated channels.