A cooperative localization algorithm exploiting a mobile device in cognitive radio networks

In cognitive radio networks (CRNs), the awareness of the environment is fundamental to efficiently avoid harmful interference toward primary users (PUs) and to improve cognitive radio (CR) performance. Thus, estimating the PUs position, rather than just knowing its presence through traditional spectrum sensing, becomes a key challenge. In this paper a novel cooperative localization algorithm (CLA) that uses few CRs is proposed to estimate PU position in harsh channel condition. CLA algorithm exploits a mobile CR (MCR) with unknown positions that collaborates with other fixed CRs to estimate PU position. To this purpose, the MCR exploits the signal strength measurements obtained from PUs through an energy-detection based spectrum sensing. Since channel parameters are not available in CRNs, a channel estimation technique is also applied. Simulations are conducted to evaluate the performance of the CLA in comparison to existing cooperative and non-cooperative localization algorithms. The MCR path is generated by the random waypoint model (RWP) and a multichannel scenario with shadow fading is implemented. Results show that the CLA outperforms the existing algorithms, due to its moving path independency and its higher localization accuracy. Moreover, simulation results confirm that CLA is robust to noisy channel conditions.