Weighted centroid source localization in cognitive radio networks (CRN)

Localization of Primary Users (PUs) can help improve the efficiency with which the spectrum is reused. Received signal strength (RSS) based methods are quite suitable for use in such networks, and centroid based localization algorithms have been suggested. The cognitive radios (CRs) estimate the RSS, and send these estimates to a CR base-station, where the PU location is estimated. In this paper, we study the performance of centroid based algorithms in such a cognitive radio setup and derive approximate expressions for the bias and variance of the location estimates. Computer simulation results are presented to validate the expressions.