A Radio Frequency Energy Harvesting-Based Multihop Clustering Routing Protocol for Cognitive Radio Sensor Networks

In radio frequency energy harvesting-cognitive radio sensor networks (RF EH-CRSNs), clustering routing protocols can help deliver monitored data towards the sink and they are vital for network performance. However, due to the impact of dynamic channel availability, limited node transmission range, and position-dependent energy arrival, existing clustering routing protocols for nonEH-CRSNs and EH nonCRSNs cannot be applied to RF EH-CRSNs. In order to solve above challenges, an RF EH-based multihop clustering routing protocol (RFMCRP) based on nonlinear EH model is proposed in this paper. Firstly, by leveraging curve fitting tool and statistical analysis, the most reasonable nonlinear EH model is identified and it is utilized by RFMCRP to measure the harvested energy accurately. Secondly, the optimal number of clusters is theoretically derived and its value is used as benchmark to evaluate the validity of our proposal. Thirdly, energy control mechanism is introduced to manage node state, and it can help improve the stability of cluster construction. In addition, energy level function-based selection criteria are defined to select high-quality cluster heads and relays, which can help improve the energy sustainability and connectivity of the whole network. Simulation results show that RFMCRP gains obvious advantages over existing protocols in extending network lifetime and improving network monitoring capability.