Distributed Spectrum Sensing Using Radio Environment Maps in Cognitive Radio Networks

Ever increasing development of wireless devices and wireless networks have increased the value of spectral space. Many efforts have been conducted to increase spectral utilization. In this paper, a novel distributed spectrum sensing method is presented. This method efficiently increases the spectral throughput of the network. In this algorithm, distributed Kalman filter, which is modified to increase estimation accuracy, is used to estimate position, velocity, and power of primary transmitters. These data are used to select spectrum holes optimally and increase spectral utilization compared to centralized methods. Obtained results are evaluated through practical implementations and simulations. Innovations of this research include introducing and employing a linear model for estimating the position of a transmitter using received power in the line of sight and non-line of sight conditions, modifying extended Kalman filter and implementation of distributed spectrum sensing; advantages of this method are illustrated compared to other spectrum sensing methods.