A RSS-based PU localization scheme using the Kalman filter
نویسندگان
چکیده
Cognitive radio sensor networks (CRSNs), is a fusion network combining wireless sensor network (WSN) with cognitive radio, undergo radio resource starvation under condition where it is densely deployed and primary user (PU) communications are concentrated. To overcome this problem, we propose a received signal strength (RSS)-based PU localization scheme using the Kalman filter to reduce noise portion of RSS from a PU. The experimental results shown in this paper prove the proposed scheme outperforms path loss exponent calibration scheme and a fixed path loss based scheme for the performance of average localization error.
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