Optimization of RF-Powered Cognitive Wireless Sensor Networks Based on Network Coding and LEACH Algorithm

The limited spectrum resource is shared by energy harvesting (EH), spectrum sensing, and data transmission in RF-Powered cognitive wireless sensor networks (CWSNs). Aiming at improving the energy and spectrum efficiency under the energy causality and the collision causality, an EH-first optimization scheme for RF-Powered CWSNs is proposed in this paper. Firstly, it combines network coding with low energy adaptive clustering hierarchy (LEACH) algorithm to achieve the load and energy balance in the data transmission process of energy-constrained sensor units. Then, in order to improve the spectrum efficiency, a spectrum resource allocation strategy based on the EH-first model is proposed in our scheme. The simulation results show that our scheme outperforms other state-of-the-art schemes in terms of average throughput. Furthermore, it reduces the energy outage probability by 5.3%-10.1% and 2.25%-4.5% compared with the cluster-based static optimization scheme and cluster-based joint optimization scheme respectively.