Adaptive Sensing Period Adjustment Scheme in Cognitive Radio Sensor Networks
Bosung Kim, Gyu-Min Lee and Byeong-Hee Roh
In this paper, we propose an adaptive sensing period adjustment scheme (ASPA) which adaptively adjusts sensing periods by considering the dynamics of the channel conditions in cognitive radio sensor networks (CRSNs). The ASPA with a linearly increasing and exponentially decreasing (LIED) algorithm is a simple but robust scheme because secondary users (SUs) can adaptively adjust their sensing periods, even when sensing errors or collisions with control messages exist. A performance model for analyzing the efficiency of the ASPA is also proposed, and it is compared with simulation results. It is shown in our results that the ASPA outperforms the existing protocol in terms of the average sensing overhead and throughput as well as the average energy consumption.
Keywords: Cognitive radio, sensing period adjustment, sensing windows, spectrum sensing, success-runs Markov chain, wireless sensor network