Abstract
A cognitive radio based hybrid data-type clustering (CR-HDC) algorithm is proposed to maximize network energy efficiency of cognitive radio (CR) sensor networks (CRSNs). By analyzing the overall energy consumption of CRSNs under various conditions, the optimal transmission range of a sensor node can be obtained for both when spectrum handoff (SHO) is applied and when it is not. Simulation results show that CR-HDC achieves performance enhancements in terms of network lifetime and the number of packets received at the base station (BS) compared to when applying the centralized low energy adaptive clustering hierarchy (LEACH-C) or hybrid data-type clustering (HDC) to CRSN environments.
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