Energy Efficiency-centric Channel Selecting in Energy Harvesting Cognitive Radio Sensor Network

Abstract

We investigate the energy efficiency (EE) channel selection problem in energy harvesting cognitive radio sensor network (EH-CRSN). The current channel allocation studies usually only consider a couple of transmitter-receiver pairs or multiple sensor nodes (SNs) with single sink. We study the network scenario with multiple sinks and multiple SNs. In view of the property that energy resource constraints in energy harvesting network, we seek the EE optimization method mechanism. The main idea of the EE-centric optimization is each SN selects channel according to the local EE to make the overall system EE improved and get the convergence at last. In this paper, we firstly introduce a RF-powered EN-CRSN and the EE formulation. Then, we proposed a game model and analyze its properties. Next, we design a SLA based channel select algorithm. Finally, simulation results show that the proposed framework can effectively improve system EE compared with the throughput-centric optimization scheme.