Constrained cluster based blind localization of primary user for cognitive radio networks

Blind localization of primary user (PU) is a geo-location spectrum awareness feature that can be very useful in enhancing the functionality of cognitive radios (CRs) in terms of minimizing the interference to the PU. However, the estimation of the PU position within the region is made difficult because cooperation between the PU and the secondary user (SU) does not exist and therefore the PU signal parameters remain unknown to the SU. The centroid-based localization techniques have significantly been adopted as suitable candidates that do not require knowledge of such parameters. In this paper we investigate the localization performance of such techniques by imposing constraints to the selection of the SU nodes, termed as SU cluster, to estimate the PU location. In particular, we impose a minimum distance constraint between any two SU nodes and group the qualifying nodes into a cluster. Only the SU nodes from the constrained cluster can take part in localizing the PU. We simulate the proposed method for a shadow fading wireless environment and compare the results with the centroid and the weighted centroid based blind localization methods. Our results show that the mean squared error in the estimation of the position of the PU is significantly improved for the proposed method compared to the two standard centroid localization techniques especially when the true PU location is away from the center of the region.