Improved local spectrum sensing in cluttered environment using a simple recursive estimator

Recently, the issue of spectrum sensing (SS) in cognitive radio networks (CRNs) has been widely reported in the literature. This paper presents a new strategy to improve the reliability of SS. One of the challenges in CRNs is to sense all information about a secondary user (SU) that is moving, especially in a cluttered environment, because the mobility of that user has a considerable impact on the sensing performance of the primary user. Thereby, an algorithm that ensures a high sensing level, in the case of a SU moving with a low velocity in a cluttered environment, is proposed. Besides, the shadowing element becomes important in cluttered environments. Therefore, it is important to provide a weighted averaging mechanism to obtain a stable measure of the signal strength at the SU. To do this, a simple recursive estimator is used. In the end, the algorithm proposed is evaluated through simulations and results.