Bregman divergence based sensor selections for spectrum sensing
This article considers spectrum-on-demand in a cellular system. A communication system that wants to access spectrum to which it does not own a license must perform spectrum sensing to identify spectrum opportunities, and to guarantee that it does not cause unacceptable interference to the license owner. Because a single sensor may be in a fading dip, cooperative sensing among multiple sensors which experience uncorrelated fading is required to guarantee reliable sensing performance. At the same time, as few sensors as possible should be used to reduce the battery consumption, while still employing enough many for the sensing to be reliable. Since shadow fading is correlated for closely spaced sensors, it is desired to select sensors which are sufficiently spatially separated. The present article addresses the problem of selecting appropriate sensors from a candidate set to engage in cooperative sensing, using different degrees of knowledge about the sensor positions. Three different algorithms for sensor selection are presented and evaluated by means of simulation. It is shown that all algorithms outperform random selection of the sensors.