High Order Geometric Range Free Localization in Opportunistic Cognitive Sensor Networks

Abstract

Position information of the primary user (PU) is important to the transmission among secondary users (SU) in cognitive sensor networks (CSN). A range free geometric localization algorithm aiming at collecting position information of PUs is proposed in this paper. Since PUs do not cooperate with SUs in CSN, opportunistic spectrum access (OSA) protocol is applied in this algorithm. Another difficulty in localization in CSN is the unavailability of received signal strength (RSS) or other precise measurements in the sensor node's physics layer due to the power and size limitation of sensor nodes, so the algorithm in this paper is designed to be range free. This range free feature makes the algorithm robust against the uncertainty of parameters of the physics layer. With respect to the performance of the algorithm, an approximation of mean squared error (MSE) of localization is derived. The roles played by the parameters in the system are analyzed. Simulation results are also presented.